presentation-order effects for aesthetic stimulus preference

Presentation-order effects for aesthetic stimulus preference

Mats P.Englund &?ke Hellstr?m

Published online:4July 2012

#Psychonomic Society,Inc.2012

Abstract For preference comparisons of paired successive musical excerpts,Koh (American Journal of Psychology,80,171–185,1967)found time-order effects (TOEs)that correlated negatively with stimulus valence —the first (vs.the second)of two unpleasant (vs.two pleasant)excerpts tended to be preferred.We present three experiments designed to investigate whether valence-level-dependent or-der effects for aesthetic preference (a)can be accounted for using Hellstr?m ’s (e.g.,Journal of Experimental Psycholo-gy:Human Perception and Performance,5,460–477,1979)sensation-weighting (SW)model,(b)can be generalized to successive and to simultaneous visual stimuli,and (c)vary,in accordance with the stimulus weighting,with interstimu-lus interval (ISI;for successive stimuli)or stimulus duration (for simultaneous stimuli).Participants compared paired successive jingles (Exp.1),successive color patterns (Exp.2),and simultaneous color patterns (Exp.3),selecting the pre-ferred stimulus.The results were well described by the SW model,which provided a better fit than did two extended versions of the Bradley –Terry –Luce model.Experiments 1and 2revealed higher weights for the second stimulus than for the first,and negatively valence-level-dependent TOEs.In Experiment 3,there was no laterality effect on the stimulus weighting and no valence-level-dependent space-order effects (SOEs).In terms of the SW model,the valence-level-dependent TOEs can be explained as a consequence of differ-ential stimulus weighting in combination with stimulus valence varying from low to high,and the absence of valence-level-dependent SOEs as a consequence of the absence of differential weighting.For successive stimuli,there were no important

effects of ISI on weightings and TOEs,and,for simultaneous stimuli,duration had only a small effect on the weighting.Keywords Aesthetic preference .Presentation order .Time-order errors .Space-order errors .Visual perception .Audition .Math modeling

Fechner (1860)was the first to notice the ubiquitous and enigmatic systematic errors that occur in comparisons of successive and simultaneous stimuli,which make two phys-ically equal stimuli subjectively different when compared:the Zeitfehler (time-order error)and the Raumfehler (space-order error).The time-order effect (TOE)and space-order effect (SOE)were defined as positive (vs.negative)for overestimation (vs.underestimation)of the first or left stim-ulus,respectively,relative to the second or right stimulus.Fechner (1876)also introduced experimental aesthetics,with scaling of aesthetic appreciation.However,he never combined those two subjects,which we attempt to do in the present article.

Since Fechner ’s (1860)discovery,TOEs have been found for a wide range of modalities,including heaviness,tone loudness,line length,duration (see,e.g.,Guilford,1954;Hellstr?m,1985,for reviews),and brightness (Maeda,1959).SOEs have been found in comparisons of,for exam-ple,line length (Hellstr?m,2003;Masin &Agostini,1991)and brightness (Kellogg,1931;Mattingley,Bradshaw,Nettleton,&Bradshaw,1994).These presentation-order effects are,however,not restricted to comparisons of stimuli varied on a well-defined physical continuum.TOEs have also been found for preference judgments of visual stimuli (McLaughlin &Kermisch,1997),auditory stimuli (Beebe-Center,1932/1965;Koh,1967;Koh &Hedlund,1969),and odors (Beebe-Center,1932/1965).For example,Koh (1967)

M.P.Englund :?.Hellstr?m (*)

Department of Psychology,Stockholm University,SE-10691Stockholm,Sweden e-mail:hellst@psychology.su.se

Atten Percept Psychophys (2012)74:1499–1511DOI 10.3758/s13414-012-0333-9

investigated the possible existence of TOEs for musical pleasantness.She had participants rate the pleasantness of tape-recorded vocal excerpts (each lasting 60s)and piano excerpts (each lasting 15s)on a 9-step scale from most pleasant (1)to most unpleasant (9).Pairs of excerpts with equal mean ratings were then selected and presented suc-cessively,with an interstimulus interval (ISI)and an inter-trial interval (ITI)of about 6and 10s,respectively,to another sample of participants;these participants were to judge the direction and degree of the pleasantness difference between the excerpts in each pair,using a 7-step scale.For the vocal as well as the piano excerpts,large TOEs occurred that were highly correlated with the mean pleasantness rating:Participants consistently tended to prefer the second (a negative TOE)out of two pleasant excerpts and the first (a positive TOE)out of two unpleasant ones.On average,there was a slight tendency toward a negative TOE.Koh and Hedlund obtained similar results.Other experiments,reported by Beebe-Center (1932/1965),in which the pleas-antness of auditory stimuli was compared,showed TOEs varying with the length of the ISI;TOEs were positive with an ISI of 1.5s,but negative with ISIs of 2s and longer.The results of these pleasantness comparisons resemble those of magnitude comparisons on traditional psychophysical con-tinua —for instance,loudness (Hellstr?m,1979;Needham,1935),heaviness (Hellstr?m,2000;Woodrow,1933),and auditory and visual duration (Hellstr?m,2003).Analogous magnitude-dependent SOEs have been found in compari-sons of line lengths (Hellstr?m,2003).

Although negative TOEs have been found more often than positive ones,a consistent finding has been that TOEs vary systematically with the intensity or magnitude level of the stimulation (see,e.g.,Hellstr?m,1985).This was the basis for Hellstr?m ’s (1979)sensation-weighting (SW)mod-el .Hellstr?m studied in detail the effects of stimulus mag-nitude on the TOE for loudness under different temporal stimulus presentation conditions.This led to the explanation of the TOE as a side effect of sensation weighting:The scaled subjective difference,d 12,between two compared stimuli is not the simple difference between their magni-tudes,but can be modeled as the difference between two weighted compounds,one for each stimulus,where stimulus i (i 01,2)and a reference level (ReL)ψri are weighted by s i and (1–s i ),respectively:

d 12?k

s 1y 1t1às 1eTy r 1?

?às 2y 2t1às 2eTy r 2??èé

tb ;

e1T

where k is a scale constant,ψ1and ψ2are the sensation magnitudes of the stimuli,and b is a term that accounts for effects apart from the weighting process (e.g.,a possible response bias).The reason for the weighting-in of the ReLs is thought to be that information about average stimulus

magnitudes partially replaces the information about the spe-cific stimulus magnitudes,in particular when this informa-tion is missing or noisy due to,for instance,memory loss (Hellstr?m,1985,1989).Therefore,perceptual testing for changes in the difference between two stimuli by using the modified test variable defined by Eq.1,instead of using the simple difference k (ψ1–ψ2),improves the discriminability of such changes (Hellstr?m,1985,1989;Patching,Englund,&Hellstr?m,in press )if the s values are optimized.A side effect,however,is the TOE or SOE,which can be defined,in subjective units,as the value of d 12in a pair of stimuli of equal magnitude (Hellstr?m,1985);using Eq.1,setting ψ10ψ20ψ,and simplifying by assuming that ψr 10ψr 20ψr yields TOE ?d 12?k s 1às 2eTy ày r eTtb :

e2T

As mentioned above,in early research (typically with ISIs of at least a couple of seconds)negative TOEs were generally found,more so the higher was the pair ’s magni-tude position in the series,and positive TOEs were found only for stimuli of low magnitudes (see,e.g.,Woodrow,1933).These results are explained in terms of Eq.2as a consequence of the weight relation s 1ψr ;cf.Hellstr?m,2000).For brief stimuli and ISIs,Hellstr?m (1979,2003)found the opposite effect of stimulus magni-tude and interpreted this as being due to the weight relation s 1>s 2.For simultaneous line lengths,Hellstr?m (2003)found the weight relation s left >s right ,which may explain the finding that the SOEs were more positive for the longer lines.

Results showing that TOEs and SOEs vary with stimulus magnitude —in particular,those results showing changes in the signs of the TOE or SOE (e.g.,Hellstr?m,2000,2003;Koh,1967)—seriously reduce the explanatory power of models that treat the TOE or SOE as a simple additive bias term (e.g.,Beaver &Gokhale,1975;Davidson &Beaver,1977).Instead,the results provide evidence in favor of the SW model.

However,even though differential weighting of subjec-tive stimulus magnitudes,along with Eq.2,seems to offer an explanation (on the group level)to the results of Koh (1967;Koh &Hedlund,1969),the presence of such weight-ing has not yet been investigated explicitly in individual comparisons of aesthetic stimuli.This weighting hypothesis suggests that preference comparisons are performed using judgment processes similar to the comparisons made in stimulus discrimination.Testing this weighting hypothesis thus promises to further the understanding of aesthetic com-parison as well as that of stimulus comparison in general.Therefore,in the present study,we present three experi-ments designed to investigate the weighting hypothesis:in Experiment 1,via successive jingles;in Experiment 2,via

successive visual patterns;and in Experiment3,via simul-taneous visual patterns.Specifically,in view of the results of Hellstr?m(e.g.,1979,2003),with different patterns of weighting and TOEs for different kinds of stimuli and large interindividual variability,we scaled the aesthetic values (valences)of the stimuli for each participant separately and investigated(a)whether TOEs analogous to those of Koh (1967)would be obtained with this within-subjects design and using briefly presented auditory stimulus sequences (jingles)and color patterns,with short ISIs;(b)whether or not the SW model can be used to account for the potential valence-level-dependent order effects and can offer a better fit than alternative models;(c)whether valence-level-dependent order effects(specifically,SOEs)for aesthetic preference also occur for color patterns with simultaneous presentation;and(d)whether the stimulus weighting and the order effects in aesthetic comparisons vary with ISI(succes-sive stimuli)or duration(simultaneous stimuli).

General method

In each experiment,two samples of undergraduate psycholo-gy students participated to fulfill a course requirement.The participants in the first sample of each experiment took part in one experimental session,comprising from one to five com-parison tasks with different kinds of stimuli(for the other tasks,see Hellstr?m,2003),and the second sample participat-ed only in the three experiments presented here,all in one session.Participants made preference judgments of pairs con-sisting of successive jingles(Exp.1)and of successive and simultaneous color patterns(Exps.2and3,respectively).The stimuli were presented in pairs on a Commodore Amiga2000 computer with a Commodore1081color display screen in a quiet,softly lit room.The participant viewed the screen from a distance of approximately45cm.There were five stimuli in each experiment,each stimulus was paired with every other stimulus,and each pair was presented with four different ISIs (Exps.1and2)or durations(Exp.3).Thus,80stimulus pairs in total were presented in each experiment.After having read instructions presented on the screen,participants were offered an opportunity to ask questions regarding anything in the instructions that they might have felt was unclear.The partic-ipant started the experiment when ready.In each trial,the participants indicated the preferred stimulus by pressing a keyboard key—“1”for first,“2”for second,or“0”for cannot decide—and then finalizing the response by pressing Enter, before which point a correction could be made. Difference scaling and data treatment

The scaling and model fitting were done individually for each participant.For each stimulus pair,the preference,or subjective attractiveness difference,d12was scaled by d*,+100 for first(1),–100for second(2),and0for cannot decide(0). Thus,the mean of d*over the pairs was analogous to the D%,or percent difference,measure,which indicates the difference between the percentages of first-stimulus-greater and first-stimulus-less responses in a set of stimulus pairs(Guilford,1954,p.306).

Equation1can be simplified to

d*?B1y1àB2y2tC;e3Twhere B10ks1,B20ks2,and

C?k y r1ày r2ts2y r2às1y r1

àá

tb:e4TIn the employed scaling method,with m sets(ISIs or durations)and n stimuli,the estimated valence value, p*(corresponding toψin Eq.3)for each stimulus is obtained by scoring+100for each choice of this stimulus,–100for each choice of the other stimulus in a pair,and0for cannot decide,summing over the2m(n–1)occurrences of a pair containing the stimulus(here,32)and dividing by200.Thus, for stimulus a:

p*a?

1

200

X m

k?1

X n

j?1;j?a

d*ajkàd*jak

;e5T

where subscript j denotes the stimulus compared with a,and k is the set.Summing the n values of p*a,the terms in the numerator cancel out,so that the mean p*value is0.For a stimulus that is chosen every time and for one that is never chosen,p*becomes m(n–1)and–m(n–1),respectively, so that in the present case the maximum and minimum possi-ble values of p*are+16and?16.It should be emphasized that the scaling method is only based on counting preference choices and is independent of the choice of model to fit the resulting data.

In fitting the SW model for each participant and set (ISI or duration),a linear regression was computed across the20pairs with d*for the pair as the dependent variable and the p*values of the stimuli in the pair (representing theirψvalues)as independent variables; thus,

d*ijk?B1k p*iàB2k p*jtC k;e6Twhere subscripts i and j denote the compared stimuli, subscripts1and2their temporal or spatial(left and right,respectively)positions in the pair,and subscript k the set.As the mean of the n values of p*is zero,for each set C k equals the mean value of d*ijk.

There is a built-in restriction,which fixes the sum of the 2m values of B to200/n,so that,in the present experiments, the sum of the eight B values becomes40.To see this, assume that each stimulus has,for the particular participant,

a true subjective valence value,ψ,which is invariant over sets.With the subscript “pred ”denoting values predicted by the equation,for set k ,d *ijk ;pred ?B 1k y i àB 2k y j tC k e7a T

and

d *jik ;pred

?B 1k y j àB 2k y i tC k :e7b T

Thus d *ijk

àd *jik

pred

?B 1k tB 2k eTy i ày j

:

e8T

For stimulus a ,Eqs.5and 8yield

p *a àápred ?1200X

m k ?1

B 1k tB 2k eTX n j ?1;j ?a

y a ày j :

e9T

The last factor in Eq.9,

P

j ?1:n ;j ?a y a ày j

,is equal to

n à1eTy a àP

j ?1:n ;j ?a y j .Because the n values of ψj sum to 0,the sum of the n –1values of ψj ,j ≠a ,becomes –ψa ,so the last factor in Eq.9becomes n à1eTy a ty a ?n áy a .This yields

p *a àápred ?n X

m k ?1

B 1k tB 2k eTáy a :

e10T

Thus,when P

k ?1:m B 1k tB 2k eTis equal to 200/n ,p *a àápred becomes equal to ψa .Equation 10justifies the use of p *,as defined here,as an estimate of ψand fixes the sum of the eight B values to 200/n —here,40.

The overall TOE in subjective units for each ISI or duration was computed as the mean scaled preference,across all stimulus pairs,of the first (left)stimulus over the second (right).This measure is equivalent to D%,the dif-ference between the percentages of “1”and “2”responses,and is termed TOE%.The measure is also equal to C (Eq.4),the d *value predicted from Eq.6for a pair of stimuli with valence values equal to the mean valence —that is,zero.

Plots of the order effect against stimulus valence

The plots of the order effects (TOEs or SOEs)against the mean valences of the stimulus pairs were produced using the following procedure:For each participant,the stimulus pairs were ranked from the least to the most liked,using the rank order of the mean of their p *values (described above).For each pair,a and b ,the TOE%or SOE%value was calculated as the mean scaled preference,across the four ISIs or dura-tions,of the first (left)stimulus over the second (right)—that

is,TOE%or SOE%eT?P k ?1:4d *ab td *

ba àá??8=.The TOEs

or SOEs and valence values for the stimulus pairs of

corresponding rank orders were averaged across partici-pants,and then the TOE or SOE values were plotted against the mean valence of the stimulus pairs.

Experiment 1:Successive jingles

It was predicted that,in accordance with the results of Hellstr?m (1979,1985,2003),the SW model would yield a good fit,with differential weighting of the stimuli.It was further predicted that,in accordance with the results of Hellstr?m (1979,2003)for tone loudness,there would be a greater weight for the first stimulus than for the second for short ISIs,and vice versa for long ISIs.This would render the results for long ISIs similar to those of Koh (1967)—thus,with negative TOEs for well-liked stimuli and positive TOEs for dis-liked stimuli.Method

Participants Two samples (n 1034,n 2046)participated to fulfill a course requirement.In total,37men and 43women took part,all with normal hearing,and most of them psy-chology students —undergraduate (fulfilling a course re-quirement)or graduate (volunteering)—from the ages of 19–64years (M age 028.6,SD age 08.7).

Stimuli and design The stimuli were five different jingles,sequences of seven sine-tone notes,played through the built-in loudspeaker at a comfortable level (measured at approximately 80dBA from the position of the participant ’s head).The tempered scale with A 40440Hz (subscript indicating the octave)was used to produce the jingles,which were (Jingle 1[J1])D 5–C 5#–B 4–A 4–G 4–F 4#–E 4;(J2)E 5–F 4–F 4#–G 4–E 4–C 5–G 4;(J3)D 5–C 5–D 5–E 5–F 4–E 4–F 4;(J4)C 6–B 5–G 5–C 6–E 5–G 5–D 5;and (J5)F 6#–E 6–D 6–C 6#–B 5–A 5–B 5.The notes within each jingle lasted 150ms each and succeeded each other immediately.Thus,the duration of each jingle was 1,050ms.The ISIs were 500,1,000,2,000,and 4,000ms.Eighty pairs (one set for each ISI of the 20pairs of different jingles,using both within-pair orders)were presented in a random order (different for each participant)with ISIs inter-mixed.The experiment,excluding instructions,lasted 12.1min on average (SD 00.7).Results and discussion

As hypothesized,we found a valence-level dependent TOE,where the TOE correlated negatively with the valence level

of the stimuli (see Fig.1);1the regression slope was signif-icant,t (9)0?6.99,p <.001,but the intercept was not,t (9)0?1.13,p 0.292.These results are analogous to those of Koh (1967),as well as to results found for compar-isons of classic psychophysical stimuli (e.g.,Guilford,1954;Hellstr?m,1979,1985,2003).According to the SW model (e.g.,Hellstr?m,1979,2000),these results can be explained in terms of differential weighting of the stimuli,with a higher weight for the second stimulus (see Eq.2).This explanation received support by analyses of the stimulus weighting.Specifically,estimates of B 1and B 2,which are proportional to the weights s 1and s 2,were obtained by regression,for each participant and ISI,of the preference ratings (d *)on the valence values (p *)of the compared stimuli.The mean across participants of the mean multiple R across ISIs was .705(SD 0.141,range .287–.930).The intrapartici-pant SD of the valences of the five stimuli,SD valence ,which can be seen as a measure of the consistency of preference judgments,and thus also of the degree to which the data lend themselves to modeling,had a mean value of 8.7(SD 02.2).The correlation across participants of SD valence with the mean R across ISIs was .944.

Alternative modeling To our knowledge,no readily appli-cable models,other than the SW model,have been proposed that would be capable of accounting for the present results.Most other existing models of preference choice,such as the Bradley –Terry –Luce (BTL)model (Bradley &Terry,1952;Luce,1959)can be ruled out,because they are built on the assumption that stimulus comparison only involves a simple subtraction of the (transformed)stimulus magnitudes,and therefore cannot account for presentation-order effects.However,the BTL model was extended by Davidson and Beaver (1977)by including a parameter to account for the order effect:the multiplicative order-effect parameter γij (with the presentation order i ,j ):

P i >j j i ;j eT?p i p i tg ij p j àá

;

e11Twhere πis the magnitude (here,valence)of the specific

stimulus (i and j ).This model will here be called the

extended BTL (EBTL)model .An order effect is reflected by γij deviating from 1,where γij >1means an advantage for stimulus j and γij <1a disadvantage for that stimulus (i.e.,a negative and a positive TOE/SOE,respectively).As it stands,the EBTL model cannot account for the present results,because a given γij value yields a positive or a negative order effect,which will not change sign with the stimulus magnitude (π).In particular,multiplying πi and πj by the same factor (i.e.,changing the general valence level)will not change P .Replacing the P values by the corresponding log-odds ratios (logits),logit P 0ln[P /(1–P )],yields

logit P i >j j i ;j eT? ?ln p i p j àá

àln g ij :e12TAs can be seen from Eq.12,the probability of choosing one stimulus over the other is determined only by the ratio (πi /πj ),and –ln γij merely enters as a constant added to logit P .As Englund and Hellstr?m (2012b )remarked,“The only way for this kind of model to account for the present results is by letting the γvalue change with the stimulus magnitude,and to the best of our knowledge,no one has suggested such an extension of the model ”(p.92).However,Davidson and Beaver (1977)did mention the possibility of letting γij depend on the pair (i ,j ).

In order to devise a BTL-type model that might challenge the SW model,we extended the EBTL model further,by making γij dependent on the stimulus magnitude,and adap-ted it to the present type of data to create two alternative models,called EEBTL1and EEBTL2.In EEBTL1,we let the γij values differ between ISIs and be different for stimulus pairs with values of mean scaled valence below zero (non-preferred)and above zero (preferred),γnonpref and γpref ,respec-tively.In addition,as the BTL models assume nonnegative

1

With the present scaling method,some of the stimulus pairs with neutral valence consisted of one highly liked and one highly disliked stimulus,respectively,and for these pairs,order effects were less likely.This may lead to a conservative estimate of the effect size of the valence-level-dependent TOE,but may also lead to a better fit of the regression line fitted to the data points in the plot.These two possibil-ities were tested by trimming the data by restricting the valence difference allowed between the stimuli within pairs.New analyses with these restrictions showed only marginal changes in the results;for example,allowing a valence difference of only 5resulted in the fitted regression line ?0?2.233x +0.802,R 0.871.As for the nontrimmed data,the slope was significant,t (9)0?5.01,p 0.001,but the intercept was not,t (9)00.37,p 0

.720.

Fig.1Experiment 1:Time-order effect (TOE%)plotted against mean stimulus valence.A fitted regression line is also displayed.A positive value of TOE%means a tendency to prefer the first stimulus

stimulus magnitudes,a constant,α,was added to the valence values separately for each ISI.This yielded4×3012fitted parameters,one more than for the SW model,which has11 (four C values and seven B values are fitted,as the eight B values sum to40;see above).For each participant,the five stimulus scale values and the scaled response for each pair were entered.The responses were converted from?100,0,and 100to0,50,and100,thus indicating a probability of prefer-ence for the first stimulus.The SW model was fitted to the data from each participant with SPSS19nonlinear regression (NLR),an iterative function-fitting program(yielding fitted parameter estimates equal or very close to those obtained by linear regression),and the EEBTL1model was fitted with constrained nonlinear regression(CNLR),which differed from NLR by imposing constraints for the additive constant to ensure the nonnegativity of the resulting magnitudes.The goodness of fit of each model(here,for the entire data set for each participant)was expressed by NLR and CNLR in terms of the R2statistic[01–(Residual sum of squares/Corrected sum of squares)],the mean of which was.543(SD0.169)for the SW,and.522(SD0.151)for the EEBTL model.In79%of the cases,the SW model yielded a better fit,and a paired t test yielded t(79)05.286,p<.001.The advantage of the SW model increased with the goodness of fit of both models; R2SWàR2EEBTL1correlated positively with R2EEBTL1(r0.433, p<.001).The correlations across participants of SD valence with R2SW and R2EEBTL1were.926and.919,respectively.SD valence correlated positively with R2SWàR2EEBTL1(.510,p<.001).

The EEBTL2model differed from EEBTL1byγij being linearly dependent on the sum of the two scaled valence values[γij0ε+β(ψi+ψj)],with separate values ofε,β, andα(see above)for each ISI.This makes12parameters, as for EEBTL1.For EEBTL2,the mean R2was.535(SD0 .148).In65%of the cases,the SW model yielded a better fit,and a paired t test on the R2values yielded t(79)01.440, p0.154.Again,the advantage of the SW model over EEBTL2increased with the goodness of fit of the latter: R2SWàR2EEBTL2correlated positively with R2EEBTL2(r0.312, p0.005).It also increased with SD valence(r0.515, p<.001).

For the cases with better than average fit of EEBTL2(i.e., R2>.535),the SW model(mean R20.673,SD0.092)fit clearly better than EEBTL2(mean R20.653,SD0.074), t(39)0 2.940,https://www.doczj.com/doc/ea14482324.html,paring EEBTL1and EEBTL2,the latter fit the data better,t(79)02.701,p0.008. R2EEBTL2àR2EEBTL1correlated weakly negatively with R2EEBTL1 (r0?.228,p0.042)and with SD valence(r0?.181,p0.108).

None of the EEBTL models,with one more parameter than the SW model,could match the fit to the data of the latter.The less noisy the data(e.g.,the greater the SD valence), the better the fit of all models,but in particular of the SW model,and the clearer was the advantage of the SW model over the EEBTL models,whereas there was no corresponding increase in advantage of EEBTL2over EEBTL1.The parameters of the SW model are also more easily interpretable than those of EEBTL1and EEBTL2.All of this speaks to the advantage of the SW model,which we selected for further analyses.

The B values from the SW model were submitted to a repeated measures ANOV A(multivariate approach),with Sample as between-subjects factor and Stimulus Position (first,second)and ISI as within-subjects factors.As pre-dicted,the effect of position was significant:We found a higher mean weight for the second(M05.80,SD01.25) stimulus than for the first(M04.20,SD01.25),F(1,78)0 30.54,p<.001,η2p?:281.That is,s1

Further results from the ANOV A analysis showed that the main effect of ISI was nonsignificant,F(3,76)01.74,p0.165, as was the interaction Position×ISI,F(3,76)01.27,p0.290. These results are contrary to those from comparisons of loud-ness,in which Hellstr?m(1979)found a higher weight for the first stimulus for short ISIs,but the opposite for long ones.One explanation may be that the jingles were easier to remember than the classic psychophysical stimuli.The Sample×ISI interaction approached significance,F(3,76)02.52,p0.064, which was due to a significant interaction between the effect of sample and the linear effect of ISI,t(76)02.28,p0.026,η2p ?:022.However,as this effect concerned the average weights of the first and second stimuli,rather than their difference,it is not of particular theoretical or practical interest.Indeed,there were no significant effects of the interactions Sample×Posi-tion,F(1,78)00.72,p0.397,and Sample×Position×ISI,F (3,76)01.11,p0.352.The results,taken together,suggest that the weighting advantage of the second stimulus over the first in aesthetic comparison of jingles is a highly robust effect that is not affected easily by experimental manipulations.Given that jingles are stimuli stretched out in time,the higher weight for the second stimulus is likely due to memory decay of the stimulus presented first(e.g.,Hellstr?m,1985);in SW theory, the stimulus weights are thought to be optimized to compensate for this memory decay by substituting lost information with average information of the stimulus series,which is reflected by lower weights(s values)in Eqs.1and2.Accordingly,with greater memory decay of the first stimulus,participants may place a higher focus on the better-remembered second stimulus in the comparison,and thus compare the second stimulus to the first.Therefore,optimization of the weights and focusing on the better-remembered stimulus may be two sides of the same process.If so,the weighting difference should be indicative of the comparison direction(see,e.g.,Englund&Hellstr?m, 2012a,b).

The difference in the overall TOE%between the two samples was nonsignificant,F (1,78)00.50,p 0.481,and the mean TOE%was negative (M 0?1.09,SD 016.83)but not significantly different from zero,t (79)0?0.58,p 0.563.The effect of ISI on TOE%was not significant,F (3,76)02.07,p 0.111,and the effect of ISI did not interact signif-icantly with the effect of sample,F (3,76)00.38,p 0.769.The reference level (ReL)in Eq.2was estimated using regression analysis.Specifically,simplifying Eq.4by assuming that ψr 10ψr 20ψr yields C ?k s 2às 1eTy r tb ?B 2àB 1eTy r tb :

e13T

Then,using Eq.13,ψr was estimated on roughly the same scale as the p *values,as the slope in the regression,through the origin,of participants ’individual means of C across ISIs on the corresponding means of (B 2–B 1);ψr was ?0.714(SE 00.632,p 0.262),which may be interpreted as being slightly below the average pattern in terms of valence.Including the intercept in this regression did not improve the fit significantly,p 0.974,so it may be concluded that the model without the bias term b is adequate.

Experiment 2:Successive color patterns

Experiment 2was designed to investigate whether the valence-level-dependent TOE found for jingles in Experiment 1and for musical excerpts by Koh (1967;Koh &Hedlund,1969),the weighting pattern s 1

Participants Two samples (n 1033,n 2046)of undergrad-uate psychology students participated,28men and 51wom-en,from the ages of 19–50years (M age 026.6,SD age 06.7).Stimuli Rectangles of 70(horizontal)×100(vertical)pixels (59×78mm)were divided into four rectangles with two colors,A and B,in the pattern A B B

A

The following five patterns (P1–P5)were used,defining A and B by the computer ’s 16intensity levels (0–15)of,in

order,red,green,and blue;thus,the patterns,depicted here in the order (A)(B),were P1,(6122)(81410);P2,(13159)(445);P3,(1430)(1141);P4,(5015)(51515);and P5,(12414)(7146).Including both within-pair orders,the stimulus combinations made up 20different pairs in four different sets,one for each ISI (100,300,900,and 2,700ms),yielding a total of 80stimulus pairs.Each pattern was presented for 100ms in the center of the screen,and the pairs from all of the sets were presented intermixed in a pseudorandom order that was the same for all participants in a sample,but differed between the samples (cf.Hellstr?m,2003,note 2).

Procedure The laboratory environment and the response mode were the same as in Experiment 1.The experiment,except for the instructions,lasted on average 8.9min (SD 00.7).

Results and discussion

Alternative modeling by the SW,EEBTL1,and EEBTL2models was performed as in Experiment 1.The mean R 2s were.675(SD 0.120)for SW,.637(SD 0.109)for EEBTL1,and .649(SD 0.105)for EEBTL2.In 95%of the cases,SW fit better than EEBTL1,and a paired t test yielded t (78)011.41,p <.001.Also,in 86%of the cases,SW fit better than EEBTL2,and a paired t test of the R 2values yielded t (78)0

7.61,p <.001.R 2SW àR 2

EEBTL1correlated positively with

R 2EEBTL1,r 0.257,p 0.022,and R 2SW àR 2

EEBTL2correlated positively with R 2EEBTL2,r 0.358,p 0.0012.The fit of EEBTL2in terms of R 2was significantly better than that of

EEBTL1,t (79)03.968,p <.001.R 2EEBTL2àR 2

EEBTL1corre-lated negatively with R 2EEBTL1(r 0?.250,p 0.026).

The intraparticipant SD valence had a mean value of 10.9(SD 01.6).The correlation across participants of SD valence with the mean R across ISIs was.940,and the correlations with the goodness of fit (R 2)for the SW,EEBTL1,and EEBTL2models were,in order,.903,.887,and.878.SD valence correlated

positively with R 2SW àR 2EEBTL1and with R 2SW àR 2

EEBTL2(.395,p <.001,and .512,p <.001,respectively)but

not with R 2EEBTL2àR 2

EEBTL1(?.156,p 0.169).

In accordance with expectations,we found a negative correlation between TOE and stimulus valence (see Fig.2);the regression slope was significant,t (9)0?4.11,p 0.003,but the intercept was not,t (9)0?0.47,p 0.648.2These results are analogous to those of Koh (1967)and also to those from the jingle comparisons of Experiment 1,albeit with slightly lower effect sizes of the TOE%values.In order to investigate the

2

As in Experiment 1,allowing a valence difference of 5only changed the fitted regression line marginally (?0?1.869x –2.074,R 0.715).As for the nontrimmed data,the slope was significant,t (9)0?2.90,p 0.020,but the intercept was not,t (9)00.60,p 0.565.

stimulus weighting,the B values were estimated using the procedures of Experiment 1;the mean,across participants,of the mean multiple R s across ISIs was .812(SD 0.093,range 0.304–.919).

The stimulus weighting was then analyzed by submitting the B values to an ANOVA for repeated measures with Within-Pair Stimulus Position (first,second)and ISI (100,300,900,2,700ms)as within-subjects factors.3The ANOVA showed that the mean weight for the second stimulus (M 05.32,SD 00.80)was significantly higher than that for the first (M 04.68,SD 00.80),F (1,78)012.45,p <.001,η2p ?:138.These results are in accor-dance with our hypotheses,with the results of Experiment 1,and also with previous research on comparisons of stimuli on physical continua (e.g.,Hellstr?m,1979,1985,2000,2003).Thus,these results demonstrate further the robustness of the weighting effect (s 1

The average TOE%(M 00.40,SD 08.77)did not differ significantly from zero,F (1,78)00.16,p 0.689.An ANOV A for repeated measures,with Sample as a between-subjects factor and ISI as a within-subjects factor,showed that the main effect of ISI on TOE%was nonsignificant,F (3,75)01.52,p 0.216.There was a small difference in mean TOE%,

which approached significance,between the first sample (M 0?1.70)and the second sample (M 01.90),F (1,77)03.35,p 0.071.The marginally different overall TOE%values merely suggest a slight difference in the constant of the regression of TOE%on stimulus valence,but not in its slope.Indeed,a t test on the regression slopes of the two samples revealed no significant difference,t (16)0?0.02,p 0.767.The interaction Sample ×ISI approached significance,F (3,75)02.33,p 0.081.Analogously to the results of Experiment 1,this small difference in TOE%did not affect the slope in the regression of TOE%on stimulus valence —in a regression of TOE%on stimulus valence and its interaction with ISI,the interaction term was nonsignificant,β0?.08,p 0.504.

Estimation of the ReLs for the two samples,using the procedures described in Experiment 1(Eq.13),showed no indication that the inclusion of a bias term and/or of two different ReLs would improve the model fit,which means that the simpler SW model (Eq.2with b 00)is adequate to explain these data.The estimated ψr s for the first and second samples,respectively,were ?0.99(SE 00.93,p 0.296)and 2.06(SE 00.675,p 0.004),and the difference between these two estimates was significant,t (78)02.42,p 0.018.The negative value of ψr for the first sample represents a valence value lower than that for the average pattern,and the positive ψr for the second sample represents a valence value above that of the average pattern.The reason for this difference in ReLs between the samples is unknown,but whatever its reason,this difference and Eq.2explain the (nonsignificant)difference in the overall TOE%.More importantly,despite the difference in ReLs —and,hence,in TOE%—between the two samples,there were (as was checked by performing appropriate ANOVAs)no differen-ces in the stimulus weighting,and therefore,no differences regarding the negative correlation of the TOE and stimulus valence.Taken together,these results suggest further that the stimulus weighting is an inherent part of the comparison process,where the net effect of this weighting (s 1

Experiment 3:Simultaneous color patterns

The SOE does not seem to have been researched as exten-sively as has the TOE,at least in terms of the number of reports published on these topics.In the reports that we have found in the literature,there are some mixed results.Specif-ically,in typical psychophysical experiments,SOEs have been reported for comparisons of line length (Hellstr?m,2003;Masin &Agostini,1991),of darkness (Kellogg,1931)and of brightness (Mattingley et al.,1994).However,Patching et al.(in press )found only weak evidence of

SOEs

Fig.2Experiment 2:Time-order effect (TOE%)plotted against mean stimulus valence.A fitted regression line is also displayed.A positive value of TOE%means a tendency to prefer the first stimulus

3

Regarding the B values and their dependence on ISI and stimulus position,there were no significant differences between the two sam-ples,as tested using repeated measures ANOV As for a multivariate approach (Pillai tests).Therefore,the data sets for the two samples were collapsed for the analyses of the B values.

but more convincing evidence of TOEs in comparisons of brightness and of size.SOE-analogous effects(i.e.,overes-timation of stimuli in the left as compared to the right half of the visual field)have been found in comparisons of dark-ness,numerosity,and size(Nicholls,Bradshaw,&Mattingley, 1999;Rhode&Elias,2007;Tant,Kuks,Kooijman, Cornelissen,&Brouwer,2002).Similarly,in the literature regarding so-called pseudoneglect(i.e.,the tendency to bisect lines noncentrally),it has been reported that healthy partici-pants generally overestimate the left side of a prebisected line in forced choice tasks when judging on which side of center a line is bisected(Jewell&McCourt,2000;McCourt,Freeman, Tahmahkera-Stevens,&Chaussee,2001;McCourt& Garlinghouse,2000;see also Rueckert,Deravanesian, Baboorian,Lacalamita,&Repplinger,2002).

Regarding SOEs in preference comparisons of aesthetic stimuli,the literature seems even scarcer;we found only one study(Freimuth&Wapner,1979).Freimuth and Wapner’s participants made paired comparisons of paintings in which the pairs were composed of one painting and its mirror image.Freimuth and Wapner did not find SOEs in the paired comparisons of the mirrored paintings,but McLaughlin and Kermisch(1997)did find TOEs for similar stimuli.Analo-gous to these results are those of Patching et al.(in press), who found consistent evidence of TOEs but not of SOEs in comparisons of brightness and of size.Clearly,further in-vestigation is needed regarding SOEs in preference compar-isons of aesthetic stimuli,and preferably should be conducted in such a manner that the results of the SOE experiment can be compared directly with those of a match-ing experiment on TOEs(Exp.2).

Therefore,in Experiment3,we used the same stimuli as in Experiment2to investigate the effect of space order on aesthetic preferences for stimuli presented simultaneously and to test whether the data could be accounted for using the SW model.No strong a priori hypothesis regarding differen-tial weighting could be made,because the previous results have been mixed.In studies on comparisons of line length,a greater weight for the left stimulus was found(Hellstr?m, 2003;Masin&Agostini,1991),but such effects were consid-erably weaker in the study by Patching et al.(in press). According to the SW model,an absence of differential weight-ing means an absence of SOEs,and vice versa,unless a response bias is involved.Therefore,the lack of SOEs in Freimuth and Wapner’s(1979)study also suggested that we would find an absence of differential stimulus weighting. Method

Participants Two samples(n1036,n2046)of undergrad-uate psychology students participated to fulfill a course requirement.Of the82who participated in the experiment,23were men and59were women,from the ages of19–

48years(M age027.4,SD07.2).

Apparatus,stimuli,and procedure The apparatus,stimuli,

procedure,and preference scaling were the same as in

Experiment2,with the following exceptions:The stimuli

were presented simultaneously,side by side,horizontally

aligned in the middle of the screen,with a distance of

24mm between the inner edges of each pair of color

patterns,and the stimulus duration was varied instead of

the ISI;the durations used were100,200,400,and800ms.

The experiment,excluding the instructions,lasted12.4min

on average(SD01.0).

Results and discussion

Modeling by the SW model as well as the EEBTL1and

EEBTL2models was performed as in Experiments1and2.

The mean R2s were.686(SD0.131)for the SW,.652(SD0

.114)for the EEBTL1,and.656(SD0.111)for the EEBTL2

models.In89%of the cases,the SW model yielded a better

fit,and a paired t test yielded t(81)09.74,p<.001.In82%of

the cases,SW fit better than EEBTL2,and a paired t test yielded t(78)08.12,p<.001.R2SWàR2EEBTL1correlated positively with R2EEBTL1,r0.453,p<.001;R2SWàR2EEBTL2 correlated positively with R2EEBTL2,r0.470,p<.001.R2EEBTL2 was nonsignificantly higher than R2EEBTL1,t(79)01.250,p0 .215,and R2EEBTL2àR2EEBTL1correlated weakly negatively with R2EEBTL1(r0?.195,p0.080).

The intraparticipant SD of the valences of the five stimuli

had a mean value of11.0(SD01.6).The correlation across

participants of the valence SD with the mean R across ISIs was

.935,and with the goodness of fit(R2)for the SW,EEBTL1,

and EEBTL2models were,in order,.904,.882,and.874.The valence SD correlated positively with R2SWàR2EEBTL1and with R2SWàR2EEBTL2(.574,p<.001,and.616,p<.001,respec-tively),but not with R2EEBTL2àR2EEBTL1(?.114,p0.307). Thus,again,a clear advantage of the SW model over

the EEBTL models was found,and we may note that it

occurred despite the lack of a strong average weighting

asymmetry.

As can be seen in Fig.3,there was no significant valence-

level-dependent SOE—neither the regression slope nor the

intercept was significant,t(9)0?1.19,p0.267,and

t(9)0?1.89,p0.096,4respectively—which is in line with

the results of preference comparisons of paintings presented

simultaneously(Freimuth&Wapner,1979),but contrary to

4As in Experiments1and2,allowing a valence difference of only5did not change the results noteworthily(?0?0.618x+3.109,R0.269).After trimming the data,the slope was still nonsignificant,t(9)0?0.79,p0 .453,and,although the intercept was more positive,it was still nonsig-nificantly different from zero,t(9)00.69,p0.511.

those of comparisons of line length (Hellstr?m,2003).According to the SW model,the absence of a valence-level-dependent SOE suggests equal mean stimulus weights over durations (M s 1≈M s 2;see Eq.2).The analyses of the stimulus weighting provided support for this hypothesis.

The mean,across participants,of the mean multiple R s across stimulus durations was .816(SD 0.097,range .490–.946).Regression estimates of the B values were ana-lyzed using a repeated measures ANOVA,5with Within-Pair Stimulus Position (left,right)and Duration as within-subjects factors.There was no significant effect of stimulus position,F (1,81)00.67.This suggests that there was no general differential weighting of the left (M 04.93,SD 00.78)and right (M 05.07,SD 00.78)stimuli,which is in contrast to previous results on comparisons of lines pre-sented simultaneously (Hellstr?m,2003;Masin &Agostini,1991).In the same ANOVA,the effect of the stimulus duration was also nonsignificant,F (3,79)01.16,p 0.329,but the Stimulus Position ×Duration interaction approached significance,F (3,79)02.59,p 0.059;the interaction Stimulus Position ×Cubic Effect of Duration was significant,t (79)0?2.46,p 0.016,η2p ?:024(see Fig.4).Separate repeated measures ANOVAs for the B values for the left and the right stimuli,respectively,with

Stimulus Duration as a within-subjects factor,showed that the duration of the stimuli affected the weight for the left stimulus,F (3,79)03.76,p 0.014,η2p ?:033[the cubic effect of duration was significant,t (79)0 2.77,p 0.007,η2p ?:031],but not for the right stimulus,F (3,79)01.03,p 0.383.

The mean B weights plotted against the stimulus duration are displayed in Fig.4.Paired-samples t tests showed that the differences between B 1and B 2for the respective dura-tions were nonsignificant in all cases,ps >.05.

Using the same method as in Experiment 1,the mean of ψr was estimated to be ?1.62(SE 00.60,p 0.009),and there was no indication that the inclusion of a bias term and/or of two different ReLs (for the left and right stimuli,respectively)would improve the model fit.Hence,once again,the simpler form of the SW model (Eq.2)is adequate to explain the present data.The average SOE%(M 00.93,SD 00.88)was not significantly different from zero,F (1,81)00.92,and there was no significant effect of stimulus duration on the average SOE%,F (3,79)01.21,p 0.310.There were no differences in mean SOE%s be-tween the two samples,all p s >.05.6In accordance with Eq.2without the bias term,the absence of a significant SOE in this experiment is explained by the absence of differential weighting,overall,of the compared stimuli (s 1≈s 2

).

Fig.3Experiment 3:Space-order effect (SOE%)plotted against mean stimulus valence.A fitted regression line is also displayed.A positive value of SOE%means a tendency to prefer the left stimulus

5

A regression of SOE%on stimulus valence with Stimulus Duration as a moderating factor showed no significant interaction between the stimulus valence and the duration,β0?.123,p 0.434.This is in accordance with the SW model,as the differences between the weights for the left and right stimuli,respectively,were nonsignificant for all

durations.

Fig.4Experiment 3:Mean B weights for the left (B1)and right (B2)stimuli,respectively,plotted against presentation duration

6

A regression of SOE%on stimulus valence with Stimulus Duration as moderating factor showed no significant interaction between the stimulus valence and the duration,β0?.123,p 0.434.This is in accordance with the SW model,as the differences between the weights for the left and right stimuli,respectively,were nonsignificant for all durations.

General discussion

The main aims of the present study were to investigate(a) whether valence-level-dependent order effects,analogous to those reported by Koh(1967),would be obtained,and if so, whether the SW model could be used to account for these effects;(b)whether the valence-level-dependent order effects for aesthetic preference can be generalized to visual stimuli with successive and simultaneous presentation;and (c)to what extent the stimulus weighting and the order effects in aesthetic comparisons vary with ISI(for succes-sive stimuli)or duration(for simultaneous stimuli).The present results were convincing regarding aim(a):For all of the experiments,there was an advantage in the fit of the data to the SW model in relation to the alternative models (EEBTL1and EEBTL2)that increased with the fit of the inferior model and with the intraparticipant SD of the stimulus valences,scaled independently of models.Over the three experiments,the superiority of the SW model was clearer in Experiments2and3than in Experiment1,where SD valence was lower and all of the models fit somewhat less well.Still,in Experiment1,results reminiscent of those of Koh(1967)were obtained using brief jingles rather than long musical excerpts and using shorter and varying ISIs,and the SW model could be used successfully to account for the valence-level-dependent TOEs,in terms of sensation weighting with a higher weight for the second stimulus than for the first.

Regarding aim(b),the results were not quite as conclu-sive.Whereas the valence-level-dependent TOEs found for the jingles(Exp.1)were fully replicated for successive color patterns(Exp.2),the results regarding analogous effects for simultaneous color patterns(Exp.3)were mostly nonsignif-icant.With regard to the comparisons of aesthetic stimuli presented simultaneously in Experiment3,there was no differential weighting,overall,which is contrary to reported results for comparisons of line length(Hellstr?m,2003; Masin&Agostini,1991),but is partly in line with results for comparisons of brightness and for the size of light spots (Patching et al.,in press).These discrepancies between research results may reflect differences between stimulus modalities.For example,differential stimulus weighting for simultaneous stimuli may be more pronounced for lines and perhaps for other geometric patterns.

Regarding aim(c),it was expected that,analogously with previous research on psychophysical comparisons(e.g., Hellstr?m,1979,2000,2003),the stimulus weighting and the order effects would vary with the length of the ISI(Exps. 1and2)or with duration(Exp.3).However,there were no significant effects of ISI on the TOEs or SOEs.Regarding the stimulus weighting,we found a consistently higher weight for the second stimulus than for the first,and this effect did not vary with the length of the ISI,either,which is in contrast to previous findings in discriminations of traditional psychophysical stimuli(e.g.,Hellstr?m,1979, 2003).For example,Hellstr?m(1979)found that,for tone loudness,the weight relation changed from s1>s2to s1

An alternative,but not necessarily opposing,interpreta-tion to that of memory loss is that the weight difference indicates the comparison direction(https://www.doczj.com/doc/ea14482324.html,ersky,1977).That is,the stimulus with the higher weight may be the subject that is compared to the other stimulus,the referent.This proposition has been made previously for preference com-parisons of stimuli denoted by labels or written descriptions (e.g.,Englund&Hellstr?m,2012a,2012b;Houston, Sherman,&Baker,1989;W?nke,Schwartz,&Noelle-Neumann,1995)and has received support from explicit investigations by Englund and Hellstr?m(2012a,2012b; cf.W?nke,1996).This idea seems congruent with Hellstr?m’s(e.g.,1985)suggestion that a lower weight magnitude reflects stimulus interference or adaptation to partial memory loss with the aim of optimizing stimulus discrimination.It seems reasonable to use the stimulus best represented in memory as the starting point of the compar-ison.For example,when the second stimulus has been presented after a relatively long ISI,it seems reasonable to try to compare it to the stimulus that was presented earlier.It may be noted that Hellstr?m(1977,1978)showed that making participants focus their responses on the first or the second stimulus by having them judge whether the first or second of two tones,respectively,was the longer,the shorter,or the louder had no appreciable effects on the relative weightings of the two stimuli(where the second stimulus had a higher weight than the first).Thus,the effect of comparing the better(represented or)remembered stim-ulus to the worse on the comparison direction seems to be larger than the effect of changing the response instruc-tions.Indeed,changing the response instructions does not necessarily change the comparison direction(e.g., Houston et al.,1989).

The results of the present study have demonstrated the continuity of preference comparisons with comparisons of physical magnitudes by showing valence-level-dependent order effects that are analogous to the magnitude-level-

dependent order effects for stimuli in classic psychophysical research(e.g.,Guilford,1954;Hellstr?m,1985).For exam-ple,earlier research(see Koh,1967)showed TOEs for affective and aesthetic judgments that were either inconsis-tent or mainly negative.The latter type of result may have been due to successive stimulus presentation with the weighting pattern s1

Author note This research was supported by the Swedish Research Council and by Stockholm University.

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American Journal of Psychology,45,391–416.

《影视特效制作AfterEffects》课程标准

《影视特效制作（A f t e r E f f e c t s）》课程标准 一、课程概述 （一）制定依据 本标准依据《艺术设计专业（新媒体策划与设计方向）人才培养方案》中的人才培养规格要求和对《影视特效制作（AfterEffects）》课程教学目标要求而制定。用于指导其课程教学与课程建设。 （二）课程的性质与地位 本课程是高等职业技术学院艺术设计专业的专业技术课程。本课程的任务是使学生通过通过本课程的学习使学生掌握使用AdobeAfterEffects，实现后期制作，毕业后可从事影视后期制作、广告后期制作、栏目包装、企事业单位的宣传部门从事策划师、特效师等多个工作岗位等工作。 （三）课程设计思路

影视特效制作（AfterEffects）是一门理论与实践相结合的专业核心课程，兼顾技术与艺术的课程。能熟练地运用AfterEffects(简称AE)制作出各类视频特效，为此而设置这门课程。其总体设计思路是，打破以知识传授为主要特征的传统学科课程模式，转变为以工作任务为中心组织课随着计算机多媒体技术的发展，AE已经广泛应用于各类影视广告视频中，在后期制作中AE是较为重要和使用广泛的技术标准。大量的影视动画和电视片头的学习和制作就是通过AE来完成的，AE也是学生就业后从事影视后期制作工作中较为常用的工具软件，为此我们采用以实例为主的项目教学方法，通过大量的典型影视视频特效实例，让学生程内容，并让学生在完成具体项目的过程中学会完成相应工作任务，并构建相关理论知识，发展职业能力。课程内容突出对学生职业能力的训练，理论知识的选取紧紧围绕工作任务完成的需要来进行，同时又充分考虑了高等职业教育对理论知识学习的需要，并融合了相关职业资格证书对知识、技能和态度的要求。项目设计以由影视特技特效为线索来进行。教学过程中，要通过校企合作，校内实训基地建设等多种途径，采取工学结合，充分开发学习资源，给学生提供丰富的实践机会。在教学过程教学中，学生始终保持较高的学习热情并能不断改善作品效果，大胆提出自己想法，逐渐将创意表达至作品中。评价采取过程评价与结果评价相结合的方式，通过理论与实践相结合，重点评价学生的职业能力。 （四）课程内容选取的依据 一是以就业为导向，瞄准影视后期后期制作人才市场需；二是为“栏目包装实训”和“新媒体策划与创意”职业能力课程奠定技术基础；三是按照项目选取课程内容和组织教学，不求学科体系的完整，强调课程内容的应用性和需求性。将课程划分为六个学习情境。把电视台精彩的节目片头、广告公司的视频广告作为课堂教学项目引入课程，加强岗位综合技能和技巧的训练，使学生能够操作熟练、举一反三。 1.学习情境中的知识点与现实密切相关

影视后期特效aftereffects》课程标准

《影视后期特效——A f t e r E f f e c t s》课程标准 一、课程概述 1、课程性质： 后期制作是制作一部影视作品的重要环节之一。随着计算机和数字化技术的发展，在后期制作中已经基本摆脱了传统的线性编辑模式，而转用以非线性编辑软件为主的非线性编辑方式。 After Effects是Adobe公司推出的一款图形视频处理软件，适用于从事设计和视频特技的机构，包括电视台、动画制作公司、个人后期制作工作室以及多媒体工作室。而在新兴的用户群，如网页设计师和图形设计师中，也开始有越来越多的人在使用After Effects。属于层类型后期软件。 本课程适计算机应用专业。 2、课程任务： （1）本课程的主要任务是理解影视特技及后期合成。掌握不同素材的导入、编辑与管理。培养学生动画制作、影视后期合成的能力；使学生能适应影视与动漫制作专业的工作要求。 （2）培养学生利用数字合成及其他相关技术进行影视后期特技效果制作的实践技能。

3、设计思路 本课程是影视制作专业的一门选修课程，随着计算机多媒体技术的发展，After Effects(简称AE)已经广泛应用于各类影视广告视频中，在后期制作中AE是较为重要和使用广泛的技术标准。大量的影视动画和电视片头的学习和制作就是通过AE来完成的，AE也是学生就业后从事影视后期制作工作中较为常用的工具软件，为此我们采用以实例为主的项目教学方法，通过大量的典型影视视频特效实例，让学生能熟练地运用AE制作出各类视频特效，为此而设置这门课程。 4、工作岗位能力分析 专业能力与职业能力目标 5、课程难点与重点 课程重点 （1）了解影视视频特效制作的原理，能够运用AE进行影视特效编辑。 （2）能够将AE与其他计算机绘图及动画片制作软件结合应用。 （3）理解动画片的后期合成流程，能够独立完成一部完成的动画片创作。 课程难点 培养学生的创造性，让学生能够发挥创意，独立创作完成的、带有独立思维的动画片作品。

aftereffects试题答案

After Effects试题 AfterEffectCS6是Adobe公司的一款影视后期制作软件 一、单项选择题、共10题、每题5分 1.在AE中进行影片渲染时，以下说法正确的是（B ） A仍然可以用After effects进行其他工作 B不能使用After effects进行其他工作 C整个windows系统都不能进行其他工作 D只可以使用adobe的其他程序 2. after effects中，缩放动画是（C ） A 围绕层的定位点进行的 B 围绕原点进行的 C 围绕中心点进行的 D 没有围绕任何点，是随机的 3. 在after effects中，引入序列静态图片时，应（B ） A 直接双击序列图像的第一个文件即可引入 B 选择序列文件的第一个文件后，需要勾选“序列”选项，然后单击“打开”按钮 C需要选择全部序列图像的名称 D使用“导入”→“合成” 4. 在after effects中，复制层的快捷键是（D ） A Ctrl+V B Ctrl+B C Ctrl+C D Ctrl+D 5. 如果使用其他应用程序修改了项目中使用的素材文件，则下次打开项目文件时（B） A 仍然出现原素材 B 出现修改后的素材 C 原素材被修改，项目文件无法打开 D 提示原素材被修改是否替换素材 6. 将素材添加到合成的正确方法是（A ） A 直接拉动素材到时间轴窗口 B 直接双击素材 C 按快捷键“Ctrl+/” D 按快捷键“Ctrl+\” 7. 在after effects中，点击层小三角显示出来的转换属性哪个没有（D ） A 位置 B 透明度 C 尺寸 D 亮度 8.在Photoshop中绘制PSD文件导入After Effects 后，怎样保持各个图层信息并可以对单个图层设置效果（ C ） A 直接导入对象 B 直接导入为脚本 C 直接导入为合成 D 导入为Photoshop序列 9.为特效的效果点设置动画后。下列哪个窗口能够对运动路径进行编辑（C ） A 项目窗口 B 播放控制窗口C时间线窗口 D 特效控制窗口

《影视后期特效——AfterEffects》课程实用标准

《影视后期特效——After Effects》课程 标准 一、课程概述 1、课程性质： 后期制作是制作一部影视作品的重要环节之一。随着计算机和数字化技术的发展，在后期制作中已经基本摆脱了传统的线性编辑模式，而转用以非线性编辑软件为主的非线性编辑方式。 After Effects是Adobe公司推出的一款图形视频处理软件，适用于从事设计和视频特技的机构，包括电视台、动画制作公司、个人后期制作工作室以及多媒体工作室。而在新兴的用户群，如网页设计师和图形设计师中，也开始有越来越多的人在使用After Effects。属于层类型后期软件。 本课程适计算机应用专业。 2、课程任务： （1）本课程的主要任务是理解影视特技及后期合成。掌握不同素材的导入、 编辑与管理。培养学生动画制作、影视后期合成的能力；使学生能适应影视与动漫制作专业的工作要求。 （2）培养学生利用数字合成及其他相关技术进行影视后期特技效果制作的实践技能。 3、设计思路 本课程是影视制作专业的一门选修课程，随着计算机多媒体技术

的发展，After Effects(简称AE)已经广泛应用于各类影视广告视频中，在后期制作中AE是较为重要和使用广泛的技术标准。大量的影视动画和电视片头的学习和制作就是通过AE来完成的，AE也是学生就业后从事影视后期制作工作中较为常用的工具软件，为此我们采用以实例为主的项目教学方法，通过大量的典型影视视频特效实例，让学生能熟练地运用AE制作出各类视频特效，为此而设置这门课程。 4、工作岗位能力分析 专业能力与职业能力目标 5、课程难点与重点 课程重点 （1）了解影视视频特效制作的原理，能够运用AE进行影视特效编辑。 （2）能够将AE与其他计算机绘图及动画片制作软件结合应用。 （3）理解动画片的后期合成流程，能够独立完成一部完成的动画片创作。 课程难点 培养学生的创造性，让学生能够发挥创意，独立创作完成的、带有独立思维的动画片作品。 6、课程特色 结合实例讲解的理论知识只是组成这门课教学模式的基础，我们通过视频教学的录制、电子书的制作，项目制作等方式，将理论与实践真正结合于该门课中。使学生能够通过新颖的教学模式，将课程更

aftereffects课程标准

《after effects》课程标准 1.概述 《after effects》是动画专业学生的岗位技能课程。适用于从事设计和视频特技的机构，包括电视台、动画制作公司、个人后期制作工作室以及多媒体工作室。而在新兴的用户群，如网页设计师和图形设计师中，也开始有越来越多的人在使用After Effects制作各种效果，是一个功能性非常强大的后期合成软件。after effects课程的开设，可以极大的提高学生的就业竞争力，为今后毕业做下坚实的铺垫。 课程的性质 通过本课程的学习，培养学生的软件操作能力，对软件功能的解析和示范，可以使学生深入学习软件和制作的技巧，扩展学生实际的应用能力，使其有能力应对今后的影视动画后期制作方面的工作。 课程设计理念 根据动漫制作技术职业岗位能力分析，学习使用after effects能真正的掌握计算机应用能力，熟练的操作影视后期合成软件，提高学生专业技能和专业实力，能在相关行业领域从事影视制作、栏目包装等工作的高素质、高技能人才。 本课程以职业能力培养为主要目标，坚持以能力为本位的设计原则，以岗位需求为依据，以工作过程为导向，以产学结合为基本途径、以培养一线技术应用人才为目的，制定了本课程的课程目标、课程内容、学习情境等课程要素。本课程是以二维、三维动画设计与制作岗位群为导向，以真实的商业项目为主要教学载体，在行业专家的指导下，对相关岗位进行任务与职业能力分析，以设计、制作岗位的“工作需求”和“岗位需求”为主线，按高职学生的认知特点，以工作过程和工作任务为依据来设计活动项目，以真实的项目案例分析组织教学，倡导学生在项目活动中学会影视制作的相关知识。本课程从实用的角度出发，由浅入深，对学生进行系统的动画后期制作能力的教育。课程开发思路 动画制作是流水线式工作，每个环节都有自己的作用。根据动画制作流程，after effects是动画片制作后期中担任了不可低估的地位。虽有前期的完美之作，但是没有良好的后期工作的话，那么前期的完美就没了展示的舞台。就如一幅绘画作品一样，俗话说，三分画，七分裱。所以after effects 课程的开设不仅能让学生真正的本专业就业，还能久立于行业之中。 2.课程目标 通过课程教学，实现学生职业技能与动漫制作技术岗位群的对接，促进本专业学生全面职业素质的养成。通过教学模式的创新、教学内容的选取，教学方法的改革培养学生after effects掌握技能，使学生拥有扎实的后期制作能力，掌握影视、动画后期特效的创作能力。

AfterEffects问题解决大全10页word文档

After Effects 问题解决大全 默认分类2010-05-14 18:05:26 阅读194 评论0字号：大中 小订阅 1 MPG格式都无法导入 视频基本上全是MPG格式的，总是还是转成AVI再导入。 另外，什么终极解码我也装了，QuickTime也装了，怎么还是出现不支持的格式。 新装的AECS4，难道这个版本有问题？ 把MPG文件后缀名改为AVI即可， 2 关于AE启动时出现After Effects error:can't get Unicode file 问题解决办法！ 出现情况状态 现在以Adobe After Effects 7.0为例，在网上发现有不少人安装完Adobe After Effects 7.0后，在启动Adobe After Effects 7.0时或者新建文字报出如下一系列错误： error1：After Effects error:can't get Unicode file (80::4) error2：After Effects warning:Unknown BIB Error.invalid encoding BRV,0 (80::4) error3： After Effects error:failed to parse,transmap file. 这是怎么回事，原因和解决方法如下： 原因：你的是绿色版本的不需要安装所以你坑定没有公共文件夹但是

以下方法应该可以解决你的问题导致这样的错误是因为Adobe公共文件 （位于C:\Program Files\Common 夹里缺少Fonts和TypeSpt这两个文件夹， Files\Adobe下），为什么这两个文件夹在安装Adobe After Effects 7.0时没有被安装？原因是在安装Adobe After Effects 7.0前，您的系统里肯定还安装了其它的Adobe产品（比如Adobe Photoshop CS2 V9.0），并且这些产品都比Adobe After Effects 7.0的版本高（比如Adobe Photoshop CS2 V9.0版本为9.0，而Adobe After Effects只是7.0），问题的关键在于这些Adobe产品在安装时都安装高版本的Adobe公共文件，如果Adobe After Effects 7.0的安装程序启动时检测到已经安装了高版本的Adobe 公共文件后，就不会再对Adobe公共文件夹下的内容做出任何更改，也就造成了Fonts和 TypeSpt这两个文件夹没有被安装到Adobe公共文件夹下。 解决方法1： 打开Adobe相关产品的安装光盘（比如您安装了Adobe Photoshop CS2 V9.0，可以把Adobe Photoshop CS2 V9.0的安装光盘打开），在光盘根目录下有个commonfilesinstaller文件夹，双击进入，看到里面有个名为Adobe Common File Installer.msi的文件，（注：这个文件能够卸载Adobe公共文件夹里的内容），双击它运行，选择界面里的“卸载”选项。卸载完后，再安装 Adobe After Effects 7.0，安装完后，看看 C:\Program Files\Common Files\Adobe下是否存在了Fonts和TypeSpt 这两个文件夹，如果存在，则启动Adobe After Effects 7.0时应该不会再提示错误信息了，这时，您也可以启动Adobe After Effects 7.0试试，

AfterEffects操作常见问题集(二)

操作常见问题集(二） 格式都无法导入 视频基本上全是格式地，总是还是转成再导入. 另外，什么终极解码我也装了，也装了，怎么还是出现不支持地格式. 新装地，难道这个版本有问题？ 把文件后缀名改为即可， 关于启动时出现' 问题解决办法！ 出现情况状态 现在以为例，在网上发现有不少人安装完后，在启动时或者新建文字报出如下一系列错误：：' () ：() ： . 这是怎么回事，原因和解决方法如下： 原因：你地是绿色版本地不需要安装所以你坑定没有公共文件夹但是以下方法应该可以解决你地问题导致这样地错误是因为公共文件夹里缺少和这两个文件夹，（位于下），为什么这两个文件夹在安装时没有被安装？原因是在安装前，您地系统里肯定还安装了其它地产品（比如），并且这些产品都比地版本高（比如版本为，而只是），问题地关键在于这些产品在安装时都安装高版本地公共文件，如果地安装程序启动时检测到已经安装了高版本地公共文件后，就不会再对公共文件夹下地内容做出任何更改，也就造成了和这两个文件夹没有被安装到公共文件夹下. 解决方法： 打开相关产品地安装光盘（比如您安装了，可以把地安装光盘打开），在光盘根目录下有个文件夹，双击进入，看到里面有个名为地文件，（注：这个文件能够卸载公共文件夹里地内容），双击它运行，选择界面里地“卸载”选项.卸载完后，再安装，安装完后，看看下是否存在了和这两个文件夹，如果存在，则启动时应该不会再提示错误信息了，这时，您也可以启动试试，确定错误信息不会出现后，做最后一步工作，重新运行一次刚才用来卸载公共文件夹地那个，这次选择界面里地“安装”选项，把公共文件夹里地内容重新升级到高版本，以免使用低版本地公共文件. 解决方法： 下载地址 将解压后地文件夹拷贝到里面,再启动下如果没有这个文件夹就自己按照路径新建然后 在拷贝地不提错了很可能他地系统里面安装有其他地地软件有公共文件夹很多网友在打开模板时会出现“最初选择地输出模块不存在”地错误，这是怎么来地呢？又该怎么解决呢？今天我们一起探讨一下. 首先，我们打开英文版，新建一个合成，然后在合成上点右键，选择 然后，就会出现渲染队列地窗口，我们在这里设置一下输出路径，就选择这个文件夹吧，请确保这个文件夹存在，然后，开始渲染，成功！ 下面，我们保存一下工程文件，文件名任意，路径任意！然后关闭工程 安装后启动报错解决办法 启动出错曾经一度困扰我二十多天，我换了好几个版本地都一样出错，无论还是还是都报错，我曾苦苦探索，也曾向各大论坛和群求租.终于发现解决地办法：现在以为例，在启动 时报出如下一系列错误：：' () ：() ： . 而且只要打开就会出现，这是怎么回事，原因和解决方法如下： 原因：导致这样地错误是因为公共文件夹里缺少和这两个文件夹，（位于下），为什么这两个文件夹在安装时没有被安装？原因是在安装前，您地系统里肯定还安装了其它地

影视后期特效——aftereffects课程标准

《影视后期特效——After Effects》课程标准 一、课程概述 1、课程性质： 后期制作是制作一部影视作品的重要环节之一。随着计算机和数字化技术的发展，在后期制作中已经基本摆脱了传统的线性编辑模式，而转用以非线性编辑软件为主的非线性编辑方式。 After Effects是Adobe公司推出的一款图形视频处理软件，适用于从事设计和视频特技的机构，包括电视台、动画制作公司、个人后期制作工作室以及多媒体工作室。而在新兴的用户群，如网页设计师和图形设计师中，也开始有越来越多的人在使用After Effects。属于层类型后期软件。 本课程适计算机应用专业。 2、课程任务： （1）本课程的主要任务是理解影视特技及后期合成。掌握不同素材的导入、 编辑与管理。培养学生动画制作、影视后期合成的能力；使学生能适应影视与动漫制作专业的工作要求。 （2）培养学生利用数字合成及其他相关技术进行影视后期特技效果制作的实践技能。 3、设计思路 本课程是影视制作专业的一门选修课程，随着计算机多媒体技术的发展，After Effects(简称AE)已经广泛应用于各类影视广告视频

中，在后期制作中AE是较为重要和使用广泛的技术标准。大量的影视动画和电视片头的学习和制作就是通过AE来完成的，AE也是学生就业后从事影视后期制作工作中较为常用的工具软件，为此我们采用以实例为主的项目教学方法，通过大量的典型影视视频特效实例，让学生能熟练地运用AE制作出各类视频特效，为此而设置这门课程。 4、工作岗位能力分析 专业能力与职业能力目标 5、课程难点与重点 课程重点 （1）了解影视视频特效制作的原理，能够运用AE进行影视特效编辑。 （2）能够将AE与其他计算机绘图及动画片制作软件结合应用。 （3）理解动画片的后期合成流程，能够独立完成一部完成的动画片创作。 课程难点 培养学生的创造性，让学生能够发挥创意，独立创作完成的、带有独立思维的动画片作品。 6、课程特色 结合实例讲解的理论知识只是组成这门课教学模式的基础，我们通过视频教学的录制、电子书的制作，项目制作等方式，将理论与实践真正结合于该门课中。使学生能够通过新颖的教学模式，将课程更好的、更充分的理解吸收。

AEaftereffects教案

数 字 合 成 之 After Effects 5.5

第一章After effects 概述 概述：After effects 是用于影视后期数字合成的软件，它可以对多层的合成图像进行编辑， 制作出天衣无缝的数字合成效果；关键帧；路径概念的运用使after effects 可以方便的编辑 二维动画；它有着令人眼花缭乱的特级系统，使after effects 能够实现使用者的一切创意。一．After effects 的工作界面介绍 After effects 的工作界面如图1-1 所示 图1-1 （一）项目窗口 在工作界面的左侧是项目窗口，每次启动after effects 时，都自动建立一个名称为“untitled project.aep”de新项目，after effects就是以项目为单位进行影片制作和管理的，可以把影片需要的素材输入到项目窗口中，这些素材包括音频文件、视频文件，静态图片等类型。如图1-2 所示 图1-2

（二）时间线窗口 当建立合成的时候，同时产生了该合成的时间线窗口，在after effects 中，时间线窗口以时间为基准对层进行操作，在时间线窗口中可以调整素材层在合成中的时间位置、素材长度、叠加方式、渲染范围等许多方面的内容，几乎包括了 after effects 中的一切合成操作如图 1-3 所示； （三）合成窗口 图 1-3 Composition 窗口可以反映各种素材之间的关系，以及影片合成的效果，如图1-4 所示 图 1-4

（四）工具面板 使用工具面板中的工具可以在合成窗口或层窗口中对素材进行各种编辑，如移动、旋转、缩放，建立并编辑遮罩等，在工具面板中包括以下： ● ：选取工具：用于在合成窗口中选取、移动对象。 ● ：旋转工具； ● ：路径工具：用于为素材加上不规则的遮罩 ● ：矩形遮罩工具：可建立矩形遮罩 ● ：旋转摄像机工具 ● ：定位工具：用于改变定位点的位置 ● ：摇移工具：用于摇移并查看素材 ● ：坐标系工具：用于选择坐标系类型 二．After effects 的工作流程 1．创建项目 2.引入素材 3.创建合成 4.创建层 5.数字合成编辑 6.渲染输出影片 三．After effects 菜单介绍 1.File 菜单：包含新建项目、导入项目、输出影片等命令 2.Edit 菜单：包含各种编辑、剪切、粘贴、复制等常用操作命令 https://www.doczj.com/doc/ea14482324.html,position （工程）菜单：包含创建新工程、输出影片等设置 https://www.doczj.com/doc/ea14482324.html,yer（层）菜单：包含了层的类型，层的参数设置以及层的各种编辑命令 5.Effect（效果）菜单：包含了各种特效 6.Animation（动画）菜单：包含了各种关键帧动画设置的各种命令 7.View（查看）菜单：包含了关于comp 窗口设置的命令 8.Window（窗口）：包含了各种快捷窗口； 9.Help 菜单

AfterEffects试题答案

After Effects 试题 After Effect CS6是Adobe公司的一款影视后期制作软件 一、单项选择题、共10题、每题 5 分 1. 在AE中进行影片渲染时，以下说法正确的是（ B ） A 仍然可以用After effects 进行其他工作 B 不能使用After effects 进行其他工作 C整个windows系统都不能进行其他工作 D只可以使用adobe的其他程序？？ 2. after effects 中，缩放动画是（C ） A 围绕层的定位点进行的 B 围绕原点进行的 C 围绕中心点进行的 D 没有围绕任何 点，是随机的 3. 在after effects 中，引入序列静态图片时，应？？（B ） A 直接双击序列图像的第一个文件即可引入？？ B 选择序列文件的第一个文件后，需要勾选“序列”选项，然后单击“打开”按钮 C需要选择全部序列图像的名称 D使用“导入”宀“合成” 4. 在after effects 中，复制层的快捷键是（D ） A Ctrl+V B Ctrl+B C Ctrl+C D Ctrl+D 5. 如果使用其他应用程序修改了项目中使用的素材文件，则下次打开项目文件时（B） A 仍然出现原素材 B 出现修改后的素材 C 原素材被修改，项目文件无法打开 D 提示原素材被修改是否替换素材 6. 将素材添加到合成的正确方法是（A ） A 直接拉动素材到时间轴窗口 B 直接双击素材 C 按快捷键“ Ctrl+/ ”

D 按快捷键“ Ctrl+ ” 7. 在after effects 中，点击层小三角显示出来的转换属性哪个没有（D ）A 位置B 透明度 C 尺寸 D 亮度 8. 在Photoshop中绘制PSD文件导入After Effects 后，怎样保持各个图层信息 并可以对单个图层设置效果（ C ） A 直接导入对象 B 直接导入为脚本 C 直接导入为合成 D 导入为 Photoshop 序列 9. 为特效的效果点设置动画后。下列哪个窗口能够对运动路径进行编辑（C ）A 项目窗口 B 播放控制窗口 C 时间线窗口 D 特效控制窗口 10.AE软件是Adobe公司开发的，主要应用于（D） A 2 维动画制作 B 3 维动画制作 C 视频编辑D特效制作 二、首图视频动态制作、20分 以“主图视频制作”字样为主题,制作一个首图视频, 间为15 秒、尺寸自定。使用 AE软件完成， 时 其他说明：除以上必须的信息外、可加入其它信息，可以使用外来素材，上交时请把素材一并上交。 三、剪辑视频创意制作、20 分 剪辑合成一个25秒的视频，尺寸为1280*720,使用AE软件完成， 其他说明：可加入其它信息，可以使用外来素材，可以使用课程练习中素材。 （学习的目的是增长知识,提高能力,相信一分耕耘一分收获,努力就 一定可以获得应有的回报）

adobeaftereffects介绍和功能

软件简介 新版本的After Effects带来了前所未有的卓越功能。在影像合成、动画、视觉效果、非线性编辑、设计动画样稿、多媒体和网页动画方面都有其发挥余地。其最新版本为Adobe After Effects CS5（即）。 [编辑本段] 主要功能 1. 高质量的视频 After Effects支持从4*4到30000*30000像素分辨率，包括高清晰度电视（HD TV）。 2. 多层剪辑 无限层电影和静态画面的成熟合成技术，使After Effects可以实现电影和静态画面无缝的合成。 3. 高效的关键帧编辑 After Effects中，关键帧支持具有所有层属性的动画，After Effects可以自动处理关键帧之间的变化。 4．无与伦比的准确性 After Ecffects可以精确到一个象素点的千分之六，可以准确地定位动画。 5．强大的路径功能 就像在纸上画草图一样，使用Motion Sketch可以轻松绘制动画路径，或者加入动画模糊。 6．强大的特技控制 After Effects使用多达85中的软插件修饰增强图象效果和动画控制。 7．同其他Adobe软件的无缝结合 After Effects在导入Photoshop和IIIustrator文件时，保留层信息。 8．高效的渲染效果 After Effects可以执行一个合成在不同尺寸大小上的多种渲染，或者执行一组任何数量的不同合成的渲染。

使用技巧 After Effects快捷键 项目窗口 新项目 Ctrl+Alt+N 打开项目 Ctrl+O 打开项目时只打开项目窗口按住Shift键 打开上次打开的项目 Ctrl+Alt+Shift+P 保存项目 Ctrl+S 选择上一子项上箭头 选择下一子项下箭头 打开选择的素材项或合成图像双击 在AE素材窗口中打开影片 Alt+双击 激活最近激活的合成图像 \ 增加选择的子项到最近激活的合成图像中 Ctrl+/ 显示所选的合成图像的设置 Ctrl+K 增加所选的合成图像的渲染队列窗口 Ctrl+Shift+/ 引入一个素材文件 Ctrl+i 引入多个素材文件 Ctrl+Alt+i 替换选择层的源素材或合成图像 Alt+从项目窗口拖动素材项到合成图像替换素材文件 Ctrl+H 设置解释素材选项 Ctrl+F 扫描发生变化的素材 Ctrl+Alt+Shift+L 重新调入素材 Ctrl+Alt+L 新建文件夹 Ctrl+Alt+Shift+N 记录素材解释方法 Ctrl+Alt+C 应用素材解释方法 Ctrl+Alt+V 设置代理文件 Ctrl+Alt+P 退出 Ctrl+Q 合成图像、层和素材窗口 在打开的窗口中循环 Ctrl+Tab 显示/隐藏标题安全区域和动作安全区域 ' 显示/隐藏网格 Ctrl+'

After Effects CS4下载 AECS4中文版

After E ffects CS4下载AE CS4中文版+汉化包+注册机+序列号+安装教程after ... after Eff ects CS4注册码等安装过后第一次启动AE CS4时候就可以输入注册码了前面输入错误的注册码这时候就能用了key: 1325-1819-4633-6359-5549-3839 1325-1347-4062-3946-3416-0598 ... After Effects CS4下载A ECS4官方破解激活版 ?运行环境：Win98/Win2000/WinXP ?软件语言：英文 ?软件类型：国产软件- 图形图像- 三维制作 ?授权方式：免费版 ?软件大小：1.00 GB AE CS4新增了查找功能但取消掉了时间线前面的时码显示，合成窗口下面的一样用。另外CC系列插件被完全内置了，软件的速度也快了许多...... 下载地址（鼠标右键点击，选择使用迅雷下载）：官方多国语言完整版官方多国语言完整版汉化程序 安装激活说明： 1.安装客户端前在hosts文件中添加A DOBE激活方面的网址，以达到屏蔽在线激活验证的目的。 首先找到hosts文件，该文件详细位置是C:windowssystem32driversetchosts hosts 是个隐藏文件，请在文件夹选项中选定“显示隐藏的文件和文件夹” 用记事本打开hosts，在hosts中添加下列网址： 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 127.0.0.1 https://www.doczj.com/doc/ea14482324.html, 2.开始安装的时候，选择试用选项，无需输入序列号。 3.在进行安装选择的时候，注意选择安装位置；默认状态下，安装全部软件和组建，可以根据自己的需要取消一些程序的安装。 4.界面语言建议选择默认的英语。 5.安装完成后，在开始中找到软件快捷方式，打开软件。 6.选择输入序列号，用“序列号生成器”生成序列号，然后将序列号(Windows Serial)填写好，完成破解。 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

(完整word版)AdobeAfterEffectsCC2018中英文对照

AE CC 2018中英文对照一、File 文件 New > New Project 新项目文件（Ctrl+Alt+N） New Team Project 新团队项目文件 New Folder 新文件夹（Ctrl+Alt+Shift+N） Adobe Photoshop File 新Photoshop文件 Open Project 打开项目文件（Ctrl+O） Open Team Project 打开团队项目文件 Open Recent > 打开最近的文件 Browse in Bridge 在Bridge里浏览（Ctrl+Alt+Shift+O）Close 关闭（Ctrl+W） Close Project 关闭项目 Save 保存（Ctrl+S） Save As > Save As 另存为（Ctrl+Shift+S） Save a Copy 另存为副本 Save a Copy As XML 另存为XML（apex）文件 Save a Copy As CC(14) 另存为CC14文件 Save a Copy As CC(13) 另存为CC13文件 Increment and Save 增量保存 Revert 恢复 Import 导入> File 文件（Ctrl+I） Multiple Files 多个文件（Ctrl+Alt+I） From Libraries 从资料库 Adobe Premiere Pro Project Adobe Premiere Pro文件 Pro Import After Effects 增效工具 Vanishing Point(.vpe) 灭点文件 Placeholder 占位符 Solid 固态层

用AfterEffects做手绘风格视频特效

用AfterEffects做手绘风格视频特效 以前中央电视台有个片头用的就是手绘效果的京剧人物，做得很不错， 他用的方法我不知道，不过这里我想到了一些方法，大家不妨一起来讨论一下。 将视频转成手绘效果，还得从将图片转成手绘效果开始说起， 网上有些效果极佳的照片转手绘漫画的图片，但大多数都是需要手工重新描线然后再色彩处理， 虽然效果好，但这对于每秒25帧的视频来说就显得很奢侈了（但愿中央台的那个用的不是重新描线的方法）。 所以我们必须得用滤镜或者其它的方法来处理，不过这也告诉我们， 只要能给图象中的人物或者景物描出正确的轮廓边，那剩下的事情就非常好办了， 对于描轮廓边，我们自然想到的是AfterEffects自带的滤镜find edges。 好！我们就从它开始下手，首先请看原图和效果图。 一、AfterEffects对静止图片的处理

下面就是我全部的滤镜和排列顺序，我将一一讲解。 1，DE Grain Reducer是一个去视频噪声点的工具， 它的作用主要是为了使最后结果比较清晰，AE中也有内置的工具， 在Noise&Grain-->Remove Grain，不过操作就比较复杂，需要取样， 如果是初学者，其实也可以用高斯模糊或者快速模糊来代替，至于所需的数值， 可以在最后再来做相应的调整;。 2，第二个命令Find Edges唯一需要注意的就是要和原图以一定比例混合(我取了40%)，如果不这样做也不是不可以，具体效果怎么样大家去尝试一下就知道了;。 3，Levels的数值可以与第一个特效配合起来调整，没有一定要求， 只要自己觉得过得去就可以了。 4，第四个滤镜是为了去色，很简单，变成黑白轮廓。 5，最后一个Brush Strokes滤镜在Stylize菜单里， 用来模拟笔刷效果，具体数值见图示。这些命令打造出了如右图的一个铅笔画人物。6，如红色框所示，将铅笔画图层与原图图层以一定比例混合起来， 就成了一幅彩色手绘画了。 本来教程到这里就算结束了，不过考虑到以上例子我用的素材是静止图片， 于是我从网上找来了一段网友视频做尝试…… 二、AfterEffects对视频图片的处理 本来教程到这里就算结束了，不过考虑到以上例子我用的素材是静止图片， 于是我从网上找来了一段网友视频做尝试，结果大失所望，下面是我的处理结果。

AfterEffects;CS5模拟考试题库有答案

Adobe 创意大学计划1. 如图所示:在 After Effects 中,为文字制作类似打字机的逐字出现效果,需要使用什么属性设 置关键帧? A.只需对Start属性设置关键帧 B.需要对End和Offset属性设置关键帧 C.只需对SourceText属性设置关键帧 D.需要在PathOptions设置关键帧 正确答案:C 2. 制作打字机式的文本逐个出现动画需要什么属性设置关键帧? A.Path Option B.Source Text C.Grouping Alignment D.Anchor Point 正确答案:B

3. A. B. C. D. 正确答案:ABCD 在 After Effects 中,对于已生成的遮罩,可以进行那些调节? 对遮罩边缘 进行羽化设置遮罩的不透明度扩展和收缩遮罩 对遮罩进行反转 4. 沿一段 Mask 产生描边动画,效果如图所示。应该使用下列哪种滤镜特效? Adobe 创意大学计划 A.Stroke B.Write-on C.Brush Stroke D.V egas 正确答案:A 5. 为带有 G-Buffer 通道信息的层设置雾化效果,如图所示,可以使用特效? A.Depth Matte B.Depth of Field

C.Fog 3D D.ID Matte 正确答案:C 6. 要达成如“右”图所示的效果(左为没有映射的效果),让环境映射到人物身体上,应该使用下列何种特效? Adobe 创意大学计划 A.Smear B.Displacement Map C.Channel Combiner

D.Color Link 正确答案:B 7 如图所示的万花筒效果,应该使用下列哪个特效完成? A.Texturize B.Radio Waves C.Fractal D.Fractal Noise 正确答案:C 8. 对一个带有 Z 通道信息的三维素材,用什么特效才能做出图中前实后虚的景深效果? Adobe 创意大学计划

Adobe After Effects CS6下载

Adobe After Effects CS6下载 下载文档，然后把下面的地址复制进迅雷一类的下载软件即可下载： http://tria l https://www.doczj.com/doc/ea14482324.html,/AdobeProduct s/AEFT/11/win64/AfterEffects_11_LS7.7z After Effect s是Adobe公司推出的一款图形视频处理软件，适用于从事设计和视频特技的机构，包括电视台、动画制作公司、个人后期制作工作室以及多媒体工作室。而在新兴的用户群，如网页设计师和图形设计师中，也开始有越来越多的人在使用After Effects。属于层类型后期软件。 After Effects软件介绍 软件简介 After effects 并不是一个非线性编辑软件，它主要是用于影视后期制作。一些特效片后期制作的在后期合成中就采用After effects。After Effects 4.1是Adobe公司于一九九九年底推出的版本，是Adobe After effects 4.0的升级版。 版本简介 Adobe After Effects 4.1针对不同需求的人士，提供Standard、Production Bundle两种版本，Standard版本提供所有主要的合成控制，2D动画及专业动画制作上的特效程序，较适合从事影视动画制作的相关人士。Production Bundle版本更加入了多种混色去背景能力，提供了高级的运动控制、变形特效、粒子特效，是专业的影视后期处理工具。 功能介绍 图形视频处理Adobe After Effects软件可以帮助您高效且精确地创建无数种引人注目的动态图形和震撼人心的视觉效果。利用与其他Adobe软件无与伦比的紧密集成和高度灵活的2D和3D合成，以及数百种预设的效果和动画，为您的电影、视频、DVD和Macromedia Flash作品增添令人耳目一新的效果。强大的路径功能就像在纸上画草图一样，使用Motion Sketch可以轻松绘制动画路径，或者加入动画模糊。强大的特技控制After Effects使用多达85种的软插件修饰增强图象效果和动画控制。同其他Adobe软件的结合After Effects在导入Photoshop和IIIustrator文件时，保留层信息。After Effects提供多种转场效果选择，并可自主调整效果，让剪辑者通过较简单的操作就可以打造出自然衔接的影像效果。高质量的视频After Effects支持从4*4到30000*30000像素分辨率，包括高清晰度电视（HDTV）。多层剪辑 无限层电影和静态画术，使After Effects可以实现电影和静态画面无缝的合成。高效的关键帧编辑 After Effects中，关键帧支持具有所有层属性的动画，After Effects可以自动处理关键帧之间的变化。无与伦比的准确性After Effects可以精确到一个象素点的千分之六，可以准确地定位动画。