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学号2012204011昆明理工大学硕士研究生学位论文开题报告书专业计算机应用技术姓名刘慧娟入学时间2012年9月导师李勃拟定的论文题目考场内人员行为分析关键技术研究报告日期研究生院1、论文选题的国内外研究动态及现状人体异常行为分析是计算机视觉技术中的一种，其主要是运用计算机视觉、图像分析、图像处理等技术从视频图像序列中识别，跟踪人体目标并对其行为进行描述和理解，从而发现异常行为。
它在视频会议、医疗诊断，尤其是安防领域，吸引了国内外大量的研究工作者和生产商对其进行研究和发展，激发出广阔的应用前景，产生的巨大的经济效益和潜在的社会价值。
在国外，许多欧洲发达国家已经开展了大量的相关项目研究，国外已开展在复杂环境下的异常行为识别研究，如在智能家居中利用自适应学习和模糊时间窗来识别年长者或有特殊需要的人的行为[1]，从而提供帮助；研究贝叶斯框架与支持向量机方法来检测人体异常行为[2]；利用粒子滤波结合时差／频差同时估计来检测复杂场景中的运动目标[3]，表明粒子滤波在处理非线性运动目标跟踪效果很好。
在美国，成立了以卡耐基梅隆大学和麻省理工学院(MIT)等多个高校联合参与，由美国国防部高举研究项目署(DARPA)带头组织的视觉监控重大项目(VSAM)[2]131，该项目采用了应用于普通的民用和公共场景下的自动视频理解技术；雷丁大学研究了车辆和行人的跟踪和人车交互作用的识别；通过建立外观模型实现对多人的跟踪[4]，可以进行实时视觉监控系统跟踪，并且可以准确的定位和分割出人的身体部分[5]，对检测人是否携带物品等行为也有很好的社会价值；以色列很多厂商已经迅速占领了智能监控设备的国际市场。
很多产品被广泛应用飞机场，铁路，港口等公共场所，如美国海关边防局采用智能视频监控技术实时的监控着北方与南方边境；迈阿密机场通过使用智能监控系统提高了该机场的整体安全性能。
此外，IBM与微软等国际著名的IT行业巨头也加大力度对该领域进行核心技术研发，提高该领域的商业化应用前景。
销售工作计划书的英文翻译Introduction:The purpose of this sales work plan is to outline the strategies, objectives, and activities that will be implemented by the sales team to achieve sales targets and drive business growth. This plan includes a detailed analysis of the current market situation, target customers, and competitors, along with a comprehensive sales strategy to maximize revenue generation. By following this plan, the sales team will be able to effectively target customers, build strong relationships, and increase sales performance.1. Market Situation Analysis:1.1 Market Overview: Analyze the current market trends, customer preferences, and industry growth rate to identify potential opportunities and challenges.1.2 Customer Segmentation: Segment the target customers based on demographics, behavior, and purchasing power to create customized sales strategies for each segment.1.3 Competitor Analysis: Analyze the strengths and weaknesses of key competitors to identify market gaps and develop competitive advantages.2. Sales Goals and Objectives:2.1 Sales Targets: Set realistic sales targets for the team, taking into consideration market potential and business objectives.2.2 Revenue Generation: Develop strategies to maximize revenue generation through cross-selling, upselling, and increasing the average transaction value.2.3 Customer Acquisition: Set specific goals for acquiring new customers and expanding the customer base.2.4 Customer Retention: Define strategies to foster customer loyalty and increase customer retention rates.3. Sales Strategy:3.1 Product Positioning: Clearly define the unique selling propositions (USPs) of the products and position them effectively in the market.3.2 Sales Channels: Identify the most effective sales channels to reach target customers, such as direct sales, e-commerce, or partnerships with distributors.3.3 Sales Techniques: Develop sales techniques and methodologies to effectively communicate with customers, understand their needs, and present tailored solutions.3.4 Sales Promotion: Plan and implement sales promotional activities, such as discounts, incentives, and loyalty programs, to drive sales volume.4. Sales Activities and KPIs:4.1 Prospecting: Define the target customer profile and develop a plan to identify and approach potential customers.4.2 Sales Visits: Set the frequency of sales visits and establish objectives for each visit, such as building relationships, presenting products, or closing deals.4.3 Sales Presentations: Develop compelling sales presentations tailored to different customer segments and their specific needs.4.4 Sales Follow-up: Define processes for tracking sales leads, following up on proposals, and closing deals in a timely manner.4.5 Key Performance Indicators (KPIs): Establish KPIs to measure sales team performance, such as the number of new customers acquired, revenue generated, and customer satisfaction levels.5. Sales Training and Development:5.1 Training Needs Analysis: Identify the skills and knowledge gaps within the sales team and develop a training plan to address these gaps.5.2 Sales Training Programs: Implement training programs to improve product knowledge, sales techniques, negotiation skills, and customer service.5.3 Performance Evaluation: Establish a performance evaluation system to assess the effectiveness of the training programs and identify areas for improvement.6. Sales Forecast and Budget:6.1 Sales Forecast: Develop a sales forecast based on market trends, historical data, and sales targets to estimate future revenue generation.6.2 Sales Budget: Allocate budget for sales activities, such as marketing campaigns, sales promotions, travel expenses, and training programs.Conclusion:This sales work plan provides a comprehensive roadmap for the sales team to achieve sales targets and drive business growth. By analyzing the market situation, developing a sales strategy, setting clear objectives, implementing effective sales activities, and continuously training and developing the sales team, we will be able to increase customer acquisition, enhance customer retention, and ultimately boost revenue generation. This plan will beregularly reviewed and updated to ensure its alignment with changing market dynamics and business goals.。
T e c h n i ca l s p e c i f i c a T i o n sElectricalPhysicalCertificationEnvironmentalShipping dimensionsModelUniversal AC InputDC Input Elevation Power Azimuth Power Polarization Power Idle Power Consumption LNB Power Dimensions Standard WeightFCC Part 15 Class B, CE & VCCI Approvals for Emission & Immunity StandardsOperating Temperature -20°C to +60°C (-4°F - 140°F)Storage Temperature -40°C to +65°C (-40°F - 149°F)Shipping box: 54 cm × 44 cm × 20 cm (21” × 17” × 8”) ; 7kg (15 lbs)Optional - See Transportable Cases datasheetDisable, 13V, 14V, 18V, 19V, 20V, 21V @ 500 mA (Max.) 7024C100- 240VAC, 2.2 - 1.1A50/60 Hz 24VDC @ 8A (Max.)24VDC @ 8A (Max.)24VDC @ 6A (Max.)24VDC @ 2A (Max.)19” 1U Rack Mountable UnitH: 4.5cm (1.75”) W: 43cm (17.1”) D: 28cm (11.0”) 4.5kg (9.9 lbs)• Simple stand-alone one touch operation to find satellite and stow antenna• Typical satellite acquisition time in less than 2 minutes• Ideal for applications that require a quick, simple setup and reliable connection• Internal DVB receiver provides modem independence • Based on an embedded software solutionAn optional 19” rack mount iNetVu® Beacon Receiver (BR300L) is available and has been integrated to work with the iNetVu® Controllers. This external self contained compact unit detects the power density of the satellite beacon (930MHz - 2300MHz) and is connected to the controller via an RS232 serial port interface.• One touch stand-alone solution • Front Panel Configurable• Compatible with all iNetVu® mobile platforms • Supports DVB-S and DVB-S2/ACM frequencies • Optimal, high-precision antenna pointing• Remote access and operation via Network, Web and other Interfaces • Built-in motion and movement protection for safety • Supports inclined orbit satellites • Integrated with multiple modems• Works with GPS and GLONASS Satellite Navigation Systems • Global Position Information available for external devices • Easy to configure and operate• Interoperable with Uplogix’s remote management appliances• Supported languages by GUI interface: English, Arabic, Russian, Swedish, Chinese (Mandarin, Traditional) and Spanish • Standard 2 year warrantyOnline with the touch of a buttonOptional Beacon ReceiverFeaturesInterfacesGPS Antenna RF Rx In / Rx Out Sensor Input Motor Control Network Interface USB 2.0 (Full Speed)Serial PortSMA Connector Type F Connector DB26 Connector9-Pin Circular AMP Connector RJ45 ConnectorUSB Type B Receptacle DB9 Female Connector7000C 100- 240VAC, 2.2 - 1.1A 50/60 Hz12VDC @ 15A (Max.)12VDC @ 15A (Max.)12VDC @ 10A (Max.)12VDC @ 3A (Max.) 12VDC @ 1A The DVB-S2/ACM Tuner is an integrated part of all iNetVu® 7000/7024 Controllers. It allows the iNetVu® system the option to find the satellite with and without the use of a satellite modem. Compact and adaptable, this high performance tuner is programmable to any DVB-S or DVB-S2/ACM frequency and allows the user to pre-configure specific satellite options.HughesNetDW 6000/7000HN 7000/7000S HN 9200/9260HN 9400/9460HN 9600/9800HX 50/90/100/200/250/260HT 1100/2000ipstar IPX-5100/9200IPX-3200GilatSkyedge II/IPSkyedge II/Pro/Access Skyedge IIc (Standalone)iDirect iNFINITI 3000/5000/7000 Series Evolution X5/X7Comtech/ RadyneCDM-600L/570L/625/840DMD 20/DMD 20 LBST SkyWire MDX420Romantis/UHP/EastarUHP-1000/200STMSatLink 1000/1910/2000/2900NewtecMDM-3100 (standalone)MDM 3X00/MDM2500/MDM6000Viasat Linkstar II/IV/S2/S2A Surfbeam ll/PROSurfbeam ll Auto-acquire Tooway/PROParadise Evolution/ Quantum Series TachyonCI-1300Ruggedized RMGAdvantechS5100S5420* Please contact C-COM if you require more information about modem compatibility as these may change without further noticeAn optional GPS/Glonass based compass is available and has beenintegrated with the iNetVu Controllers. This external compact device can be fitted on roof of vehicle beside the iNetVu platform to provide accurate vehicle heading within 1 degree irrespective of the surrounding magnetic field. The precise heading of the antenna translates to a smaller search window and hence faster satellite acquisitions. Interfaces to the controller via RS-232 serial port.Optional GPS/GLONASS CompassT e c h n i c a l s p e c i f i c a T i o n s• DVB Search - Searches directly for any DVB-S or DVB-S2 (ACM) carrier on the target satellite and peaks on it.• DVB Search, Opposite Polarity – Searches for DVB-S or DVB-S2 carrier in the opposite polarity on target satellite, then rotates p olarization axes and enables transmitter if modem signal attained.• DVB Search, Reference Satellite - Searches for a DVB-S or DVB-S2 carrier on ANY configured reference satellite then moves to t he target satellite and peaks on modem signal.• RF Automatic Search – The system will stop and search for modem signal when it senses an increase in RF energyreceived through t he DVB tuner as it passes by the target satellite. If the modem signal is found, the system will begin the peak process.• RF Override Search – The user specifies an RF Threshold such that the system stops when it reaches an area above the threshold a nd looks for modem signal to peak on.• Beacon Receiver – The Controller works seamlessly with the optional iNetVu® Beacon Receiver by searching for aspecified beacon frequency and then peaks on it (search gain level can be adjusted).• Auto-Deploy Method - Peaks on a reference satellite then uses precise pointing mechanism to locate the target satellite, even when n o modem RF or beacon signal is available to peak on.• Can be operated from a PC application using the USB port Via its web interface, it can be operated remotely or locally over a network connection• Can be completely configured from the front panel with a password protected configuration menu• Protects the platform and its components from damage, using current levels and sensor readings. It includes motion and movement protection as well• Provides automatic re-peaking if signal degradation occurs• Works correctly even when deployed while on an incline (in any direction) of up to 15°• Can search for both DVB-S and DVB-S2/ACM carriers• Supports full automatic and manual control of the iNetVu® Platform• Allows the users to select from multiple speed levels for both azimuth and elevation• Allows the system to operate unattended in remote locations• Is able to upload the recorded log information (Maximum of 12 hours) from the controller to the PC for troubleshooting • Supports full tracking of Inclined Orbit satellites by both signal strength and timed function• Is capable of powering the LNB with 13-21 Volts, selectable in software• Provides the option of saving the settings to a configuration file that can be used to configure additional controllers with the same configuration parameters• Works seamlessly with Uplogix Remote Management Appliances• Supports both GPS and GLONASS Satellite Navigation Systems• Supports Electronic Flux Gate Compass for increased speed of acquisition• Designed and manufactured to the highest standards of quality and reliability by C-COM• Supports all iNetVu® Mobile antenna platforms。
英语培训推销计划书Introduction:English has become a global language and is essential for communication in today's world. As a result, the demand for English training has continued to grow. Our company, XYZ Training Institute, aims to provide high-quality English training to individuals and businesses. In this promotion plan, we will outline our strategies to increase awareness, attract more customers, and ultimately grow our business.Target Audience:Our target audience includes:- Individuals who want to improve their English skills for personal or professional development.- Businesses looking to provide English training for their employees to enhance their communication and productivity.- Schools and educational institutions seeking additional English training for their students. Key Objectives:The key objectives of our promotion plan include:- Increase brand awareness and market presence.- Generate leads and attract more customers for our English training programs.- Build strong relationships with businesses and educational institutions.- Improve customer retention and satisfaction.Strategies and Tactics:1. Digital Marketing:- Implement a comprehensive digital marketing strategy to increase our online presence. - Utilize social media platforms such as Facebook, Instagram, and LinkedIn to promote our training programs and engage with potential customers.- Create informative and engaging content, including blog posts, infographics, and videos, to showcase the benefits of our English training.- Use targeted advertising campaigns to reach specific segments of our target audience. 2. Referral Program:- Implement a referral program to encourage our current customers to refer new clients to us.- Offer incentives, such as discounts on future courses or additional resources, for successful referrals.- Develop referral marketing materials, including brochures and email templates, to support our customers in referring others to our training institute.3. Strategic Partnerships:- Establish partnerships with businesses and educational institutions to offer our English training programs to their employees or students.- Customize training programs to meet the specific needs of our partners' workforce or student population.- Offer special discounts or packages for our partner organizations to incentivize collaboration.4. Content Marketing:- Develop a content marketing strategy to position our company as a thought leader in English training.- Produce high-quality educational content, such as e-books, webinars, and whitepapers, to showcase our expertise and attract potential customers.- Share our content through various channels, such as our website, email newsletters, and industry publications, to reach a wider audience.5. Event Marketing:- Organize and participate in local events, such as job fairs, trade shows, and community gatherings, to promote our English training programs.- Sponsor or host workshops, seminars, and networking events to showcase our expertise and connect with potential customers.- Collect contact information from event attendees to follow up with targeted marketing efforts.6. Customer Relationship Management:- Implement a customer relationship management (CRM) system to effectively manage customer interactions and track leads.- Develop personalized communication strategies, such as email newsletters and follow-up calls, to nurture leads and maintain customer relationships.- Collect feedback from customers to continuously improve our training programs and services.Measurement and Evaluation:To measure the effectiveness of our promotion plan, we will track the following key performance indicators:- Website traffic and engagement metrics, such as page views, time on site, and conversion rates.- Social media reach and engagement, including likes, shares, and comments on our posts. - Lead generation and conversion rates, such as the number of inquiries and course enrollments.- Partner acquisition and retention, including the number of new partnerships and the renewal rate of existing ones.- Customer satisfaction and retention, measured through surveys and customer feedback. Budget:The estimated budget for implementing this promotion plan includes expenses for digital marketing, referral incentives, event participation, and partner collaboration. We will allocate resources based on the expected return on investment and the potential impact on our business growth.Conclusion:Our English Training Promotion Plan aims to increase awareness, attract more customers, and grow our business. By implementing the strategies and tactics outlined in this plan, we are confident that we will achieve our objectives and position XYZ Training Institute as a leading provider of high-quality English training.。
第35卷第"期机电产品开发与创新Vol.35,No.1 2022年1月Development&Innovation of M achinery&E lectrical P roducts Jan.,2022文章编号：1002-6673(2022)01-038-04基于穿戴设备的人体运动数据采集系统设计孙军，周志楠(沈阳建筑大学机械工程学院，辽宁沈阳110168)摘要：本文设计一个基于穿戴设备的人体运动数据采集系统，该系统结合了运动人体科学、生物力学及人因工程学等多学科交叉知识$系统通过可穿戴采集设备Neuron与视觉识别设备Kienct完成对人体骨骼数据的获取，通过Visu/lStuDio开发平台搭建系统框架，利用C#完成系统界面的设计，通过编写程序完成Neu-ron和Kinect对人体运动数据的采集以及实时数据的展示$本系统可以存储数据形成项目文件,并对采集的数据进行分析与研究，通过分析验证能够获得两个采集设备采集的数据变化，为工程控制等方面提供数据服务$关键词：Neuron；Kinect；人体运动数据采集系统&Visual Studio开发平台中图分类号：TH122文献标识码：A doi:10.3969/j.iss).1002-6673.2022.01.011Design of Human Movement Data Acquisition System Based on Wearable DevicesSUNJun,ZHOU Zhi-Nan(School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang Liaoning110168,China)Abstract:This paper designs a human motion data acquisition system based on wearable devices,which combines the multidisciplinary knowledge of human motion science,biomechanics and human factors engineering.The system achieves the acquisition of human bone data by using wearable acquisition device Neuron and Visual recognition device Kienct.The system framework is built by Visual Studio development platform,and the interface of the system is designed by C#.Py programming Neuron and Kinect to collect human movement data and display real-time data.The system can store data to form project files,then analyze and study the collected data.Through analysis and verification,the data changes collected by two acquisition devices can be obtained,providing data services for engineering control and other aspects. Keywords:Neuron；Kienct；Human movement data acquisition system；Visual Studio development platform0引言随着计算机软硬件技术的飞速发展，运动捕捉设备已经进入了实用化阶段，其技术成功地用于远程工业控制［11、体育训练玖教学系统冋、医疗康复冏等许多方面，很多复杂的动作可以通过动作捕捉设备采集到。
优惠券活动方案英文# Coupon Promotion Plan## IntroductionIn the competitive landscape of today's market, businessesare constantly seeking innovative ways to attract and retain customers. One proven method is through the strategic use of coupons. This document outlines a comprehensive coupon promotion plan designed to boost sales, increase customer engagement, and enhance brand loyalty.## Objectives1. Increase Sales: To achieve a 20% increase in sales volume within the promotional period.2. Customer Acquisition: To attract at least 15% newcustomers to the business.3. Brand Awareness: To raise brand visibility by 10% through social media and other marketing channels.4. Customer Loyalty: To improve customer retention rates by 5% through repeat purchases.## Target AudienceThe promotion will primarily target:- First-time buyers looking for introductory offers.- Existing customers seeking value-added deals.- Social media savvy consumers who are likely to share deals online.## Promotion Strategy### Types of Coupons- Discount Coupons: Offer a percentage off on total purchase. - Cashback Coupons: Provide cash back on the next purchase. - Buy-One-Get-One (BOGO): Encourage bulk buying by offering a second item free with the first.### Distribution Channels- Online Platforms: Social media, email newsletters, and the company website.- In-Store: Physical coupons handed out during checkout.- Partnerships: Collaborate with local businesses for cross-promotion.### Timing- Seasonal Offers: Align with holiday seasons and shopping events.- Flash Sales: Limited-time offers to create urgency.### Exclusivity- VIP Coupons: Exclusive offers for loyal customers.- Member-Only Deals: Special discounts for members of a loyalty program.## Implementation1. Design: Create visually appealing and easy-to-understand coupons.2. Budgeting: Allocate funds for printing and digital distribution.3. Tracking: Implement a system to monitor coupon usage and customer feedback.4. Promotion: Use various marketing channels to advertise the coupon offers.## Monitoring and Evaluation- Sales Data: Analyze sales figures before, during, and after the promotion.- Customer Feedback: Collect and assess feedback through surveys and social media.- Adjustments: Make necessary adjustments to the strategy based on performance.## Risk Management- Over-Redemption: Set a cap on the number of coupons per customer to prevent abuse.- Market Response: Be prepared to pivot the strategy if the market response is not as expected.## ConclusionThe success of a coupon promotion lies in its ability to resonate with the target audience while delivering tangible benefits to the business. By carefully planning and executing this coupon promotion plan, we aim to achieve our objectives and set the stage for a successful sales campaign.This plan is a blueprint for a strategic approach to coupon promotions, designed to drive sales and customer engagement through targeted offers and meticulous execution.。
自动化专业常用英语词汇1. Automation（自动化）: The use of technology to control and operate processes without human intervention.2. Control system（控制系统）: A system that manages and regulates the behavior of other systems or processes.3. Programmable logic controller (PLC)（可编程逻辑控制器）: A digital computer used for automation of electromechanical processes.4. Human-machine interface (HMI)（人机界面）: A graphical user interface that allows interaction between humans and machines.5. Sensor（传感器）: A device that detects and responds to physical input from the environment.6. Actuator（执行器）: A device that converts electrical signals into mechanical motion.7. Robotics（机器人技术）: The design, construction, and operation of robots for automation and autonomous tasks.8. SCADA (Supervisory Control and Data Acquisition)（监控与数据采集系统）:A control system architecture that combines hardware and software for monitoring and controlling industrial processes.9. Process control（过程控制）: The regulation of variables in a manufacturing or industrial process to maintain desired output.10. Feedback loop（反馈回路）: A control system mechanism that continuously monitors and adjusts the output based on the measured performance.11. PID controller（PID控制器）: A control algorithm used in feedback control systems to adjust the output based on proportional, integral, and derivative terms.12. Industrial automation（工业自动化）: The application of automation technology in industrial processes to increase efficiency, productivity, and safety.13. PLC programming（PLC编程）: The process of writing and implementing instructions for a programmable logic controller.14. DCS (Distributed Control System)（分布式控制系统）: A control system that consists of multiple control elements distributed throughout a plant or facility.15. SCARA robot (Selective Compliance Assembly Robot Arm)（选择性顺从装配机器人）: A type of robot with a rigid vertical arm and a flexible horizontal arm, commonly used in assembly tasks.16. CNC (Computer Numerical Control)（数控）: A control system that uses computers to control machine tools and manufacturing processes.17. Fieldbus（现场总线）: A digital communication network used to connect sensors, actuators, and controllers in an industrial automation system.18. HMI programming（HMI编程）: The process of designing and implementing the user interface for a human-machine interface.19. SCADA programming（SCADA编程）: The process of configuring and programming a SCADA system to monitor and control industrial processes.20. Industrial network（工业网络）: A communication network that connects devices and systems in an industrial automation environment.21. Safety system（安全系统）: A system designed to prevent accidents and protect personnel and equipment in an industrial setting.22. Motion control（运动控制）: The management and regulation of the movement of machines or robotic systems.23. Fault diagnosis（故障诊断）: The process of identifying and analyzing faults or malfunctions in an automated system.24. Process optimization（过程优化）: The practice of improving efficiency and performance in industrial processes through automation and control.25. Industrial robotics（工业机器人）: The application of robotic systems in industrial settings for tasks such as assembly, welding, and material handling.以上是自动化专业常用英语词汇的详细介绍。
现代电子技术Modern Electronics TechniqueAug.2022Vol.45No.162022年8月15日第45卷第16期0引言仿人机器人是模仿人体结构设计的可以模仿人体动作的机器，为了使机器人的动作更加接近真实的人体动作[1]，并且使仿人机器人替代人们在恶劣的环境完成重复性操作，对人体动作序列的研究是必不可少的。
人体动作序列的获取是仿人机器人动作学习的前提，通过获取人体动作序列并进行分析、处理，让仿人机器人学习和掌握人体动作[2]，是仿人机器人研究的基本思路。
因此，人体动作序列的精确获取对于仿人机器人的研究具有重要意义。
目前人体动作捕捉系统[3]大多需要人体佩戴特定传感器，这些特定传感器可以主动发射特定的信号到周围部署的摄像机，实现多目定位。
美国Motion Analysis 公司设计的光学式运动捕捉设备能够实现精确的人体运动姿态捕捉[4]。
以上方法通常比被动形式的方法精准，但是要求人体佩戴较为昂贵的专用设备。
为此，国内外专家对无标记的人体动作捕捉开展大量研究，例如：文献[5]借助OpenPose 在二维图像中实现了人体关节点的像素坐标估计；Qiao S 等提出了一种基于OpenPose 的实DOI ：10.16652/j.issn.1004⁃373x.2022.16.024引用格式：董鹏越，张雷，辛山.基于权值优化的多相机OpenPose 的三维动作捕捉[J].现代电子技术，2022，45（16）：127⁃132.基于权值优化的多相机OpenPose 的三维动作捕捉董鹏越，张雷，辛山（北京建筑大学电气与信息工程学院，北京100044）摘要：目前OpenPose 应用于人体三维动作捕捉，仍然存在精度不够的问题。
针对此问题，文中提出一种基于权值优化的多相机OpenPose 的三维动作捕捉方法。
首先，将多个相机对焦于同一捕捉区域，同步获取人体动作视频，并结合开源平台OpenPose 的人体骨架识别模块，来获取人体关节点像素坐标序列；然后，在多目视觉原理的基础上，提出基于权值优化的多目重建优化算法，实现人体关节点三维坐标的精确获取；最后，采用真实案例实现人体三维动作捕捉。
营销策略管理英文(2)Marketing Strategy ManagementMarketing strategy management is a crucial aspect of a company's overall success. It involves the planning, implementation, and control of marketing activities to achieve the company's objectives. Effective marketing strategy management helps businesses to understand and meet customer needs, stay ahead of competitors, and drive revenue growth.To begin with, a thorough understanding of the target market is essential for successful marketing strategy management. This involves conducting market research to identify customer behaviors, preferences, and buying patterns. By understanding customers' needs and wants, companies can develop marketing strategies that are tailored to their target audience. For example, if the research shows that the target market consists of young adults who value sustainability, a company can develop a marketing strategy that emphasizes its eco-friendly products or practices.Once the target market has been identified, companies need to develop a positioning strategy. This is how the company wants to be perceived by its customers relative to competitors. The positioning strategy should highlight the company's unique value proposition and differentiate it from its competitors. For example, a company could position itself as a premium brand with superior quality products or as a budget-friendly option with affordable prices.After developing the positioning strategy, companies need todecide on the marketing mix. The marketing mix consists of the "4 Ps": product, price, place, and promotion. Product refers to the features and benefits of the offering, price involves determining the appropriate pricing strategy, place focuses on distribution channels and locations, and promotion includes advertising, public relations, and sales promotion activities.Implementation of the marketing strategy is equally important. This involves executing the marketing mix tactics and monitoring their effectiveness. Companies need to establish key performance indicators (KPIs) to measure the success of their marketing activities. These KPIs could include sales revenue, market share, customer satisfaction ratings, or website traffic. Regular monitoring and analysis of the KPIs will provide valuable insights into the effectiveness of the marketing strategy and allow for necessary adjustments if needed.Finally, control is essential in marketing strategy management. Companies need to continuously evaluate and adjust their marketing strategies to adapt to changing market conditions. This could involve modifying the marketing mix, targeting different customer segments, or exploring new marketing channels. Continuous evaluation allows companies to stay competitive and meet evolving customer needs.In conclusion, effective marketing strategy management is vital for the success of any business. By understanding the target market, developing a positioning strategy, implementing the marketing mix, and continuously monitoring and adjusting the strategy, companies can drive revenue growth, satisfy customers, and stay ahead ofcompetitors.Certainly! Here is further content on marketing strategy management:In addition to understanding the target market and developing a positioning strategy, companies must also consider the competitive landscape when managing their marketing strategy. It is crucial to identify and analyze competitors to gain insights into their strengths, weaknesses, and marketing tactics. By understanding how competitors position themselves in the market and how they communicate with customers, companies can find opportunities to differentiate themselves and develop strategies to gain a competitive advantage.To effectively manage the marketing strategy, companies need to set clear and measurable goals. These goals should align with the overall objectives of the business and help drive its growth and profitability. Goals could include increasing market share, expanding into new markets, or improving customer retention rates. By setting specific goals, companies can focus their marketing efforts and track their progress towards achieving those goals. Once the goals are established, companies must develop marketing tactics to support the strategy. This involves deciding on the specific marketing channels and activities to reach the target market. For example, if the target market is active on social media platforms, companies may choose to invest in social media advertising or influencer partnerships. If the target market is more traditional, companies may opt for print advertisements or television commercials. The choice of marketing tactics should align with the target market's preferences and behaviors.When implementing the marketing tactics, it is crucial to carefully allocate resources. This includes budgeting for marketing activities, allocating personnel, and managing marketing projects. Companies should ensure that they have the necessary financial resources to support their marketing efforts and that the team responsible for executing the marketing strategy has the required skills and expertise. Effective resource management is essential to ensure that the marketing strategy is implemented efficiently and effectively.Furthermore, companies must continuously measure the effectiveness of their marketing activities. This involves regularly monitoring and analyzing key performance indicators (KPIs) to evaluate the success of the marketing strategy. KPIs could include metrics like return on investment (ROI), customer acquisition costs, or conversion rates. By analyzing these metrics, companies can identify what is working well and make necessary adjustments to improve the marketing strategy. For example, if certain marketing channels are not delivering expected results, companies may decide to reallocate their budget to focus on channels that are generating a higher ROI.Additionally, companies should also gather and analyze customer feedback to gain insights into their satisfaction level and preferences. This can be done through surveys, focus groups, or analyzing customer reviews and feedback on social media platforms. By understanding customer perceptions and preferences, companies can refine their marketing strategies and tailor their offerings to better meet customer needs.Lastly, it is important to emphasize the role of innovation in marketing strategy management. With the rapidly evolving business landscape, companies need to constantly innovate to stay ahead of competitors and address changing customer demands. This could involve introducing new products or services, adopting new technologies or marketing channels, or implementing creative marketing campaigns. By embracing innovation, companies can attract and retain customers and maintain a competitive edge in the market.In conclusion, effective marketing strategy management is a continuous process that involves understanding the target market, developing a positioning strategy, implementing marketing tactics, and monitoring and adjusting the strategy based on market conditions and customer feedback. By following these steps, companies can achieve their marketing goals, attract and retain customers, and drive business growth.。
MOTION BASED TARGET ACQUISITION AND EVALUATION IN AN ADAPTIVE MACHINE VISION SYSTEM Presented at the Video Photogrammetry and Exploitation Conference,11-12 May 1995, Washington, D.C.Michael R. Blackburn, Ph.D.D371, SPAWAR Systems Center, San Diego, CA 92152-7383(619) 553-1904mike@In this brief introduction to the topic there are sixteen points that we would like to make in reference to the problems of dynamic scene understanding and 3-D model extraction. We will first list these sixteen points, then take about a minute and a half to explain each one separately.1.Machine vision systems may achieve human-like perception most efficientlythrough progressive emulation of natural mechanisms of visual-motorcontrol.2.Motion is fundamental to all forms of natural perception.3.Independent motion marks new targets, while induced motion providesinformation about the geometry of a static environment.4.Target behavior is apparent primarily through an analysis of motion.5.The geometries of natural vision systems facilitate processing of speciesrelevant information.6.Motion information can transform pattern information to achieve perceptualconstancies.7.Visual perception is an active process.8.Reflex saccadic eye movements sample the environment.9.Expectations drive search patterns over familiar targets.10.Recognition is the verification of a prediction.11.Acquisition and use of information are inseparable processes in naturalintelligence.12.Animals learn environmental correlations to satisfy internal needs.13.Machines can learn similarly if needs are appropriately defined and tested.14.Machine learning, following biological precedent, requires a reflex base thatresponds to both internal and external events, sensor preprocessing forfeature definitions, and association matrices between abstractrepresentations of information from the sensor domains.15.Neural networks, whether biological or artificial, self organize and selectidiosyncratically relevant features for discrimination and prediction ofenvironmental contingencies.16.Recommendations and Summary of Machine vision at NRaDNow for some explanaton:1) Machine vision systems should emulate natural mechanisms.How to approach human-like perception without human liabilities?What are the human liabilities?Unreliable - errors of omission, errors of commission,Unsuitable - slow, capacity limitedExpensive - costs of training and maintenance,Fragile - costs of protection and repair.What are the human assets?Adaptable - on-the-job learning,Available - many candidates for the job.Why emulate biological mechanisms?1. Natural mechanisms have proven successful and efficient.2. A great deal is known of how they work.3. Early fidelity to natural mechanisms may facilitate constructionof higher order processes that depend upon them, and of which weyet are uncertain.Advanced information processing systems such as man are phylogenetic consequences of simpler designs. Little is thrown away in the design of more advanced systems, rather, new capabilities are built up by the addition of neural controllers that interact with earlierexisting controllers. Figure 1 lists the relative complexity of the phylum, the evident nervous system advance at that stage, and the consequential new capabilities afforded.Figure 1.If we want to achieve the capabilities of man in an artificial system without the his/her limitations, we may do so by judicious emulation of the computational processes that subserve his intelligence.2) Motion Analysis is fundamentalMotion dominates the processing of simpler organisms. In man there are specialized receptors for motion in cutaneous touch - the Meissner and Pacinian corpuscles, while other receptors - the Merkel and Ruffini - code static pressure (Vallbo, 1994); for the movement or change in stretch and tension of muscles there are the muscle spindle organs and the Golgi tendon organs, while and joint angle sensors code static position; in vision the rod photoreceptors and the magnocellular pathway are primarily involved in the processing of optic flow to visual motion, while the cone photoreceptors and theparvocellular pathway are primarily concerned with the processing of pattern and color (van Essen and Maunsell, 1983). The functional difference between static and transient detectors is adaptation. Motion detectors rapidly adapt to conditions. (Muscle spindles adapt through active mechanisms involving the Gamma motor control of the intrafusal motor fibers.)Motion is not something that was added to scene analysis, but it is what nature started with. Instead, pattern analysis was an addition to motion analysis.Figure 2 is a mediolateral view of the human brain. All of the parts of the brain that can be identified in simpler species are located in progressively more central and more posterior regions.Figure 2.3)Induced motion provides information about the geometry of a static environment.Animals exploit their own ability to move by traversing the environment - creating local changes in pattern on their sensor fields.Figure 3.A moving sensor induces an optic flow from stationary objects that depends on the objects' 3-D locations with respect to the direction of travel (see Figure 3 for examples). The ability to understand action in three dimensions based upon non-stereo motion, size, perspective, or occlusion cues is evident in ordinary cinematography. Depth is commonly dramatized by filming with the camera in motion.Subconscious processes monitor this induced motion for its use in localization of non target objects required in reflex obstacle avoidance and path planning.Most advanced vertebrates have the ability to maintain a visual fix on a target, whether the target is moving or not. The fixation is maintained through saccadic eye movements and smooth pursuit eye movements. When the fixating animal is also moving, additional information about the geometry of the environment is gained by the induced optic flow.This information is approximated in Figure 4.Figure 4.Independent motion marks new targetsAnimals use target motion as the principal cue for visual target acquisition. The superior colliculus, a midbrain nucleus responsible for selecting new visual targets, receives input from the motion detectors of the retina as well as from the cerebral cortex. Motion is a nearly irresistible factor in reflex control of visual attention. We are compelled to look at a target that moves uniquely, and while we may choose to look away, our attention is drawn back to it if it continues to exhibit erratic motion. Looking at a target means moving our eyes, head and body through saccades and smooth pursuit movements in the direction of the target so that the image of the target falls on the center of our retina (orienting reflex).Motion segmentation mechanisms force attention to sources of unique motion (generally due to animate targets) and suppress conscious awareness of the consistent background motion (generally due to movements of the sensor).Visual motion segmentation mechanisms permit target acquisition, tracking, and trailing.Figure 5 shows a visually sensing robot acquiring, tracking, and trailing a walking human in a complex visual environment, using only visual motion segmentation for input.Figure 5.4)Motion reveals target behaviorWhen the target is in motion, the analysis of target motion is fundamental to the assessment of its behavior.This is obvious. What it implies however is that we need mechanisms first to analyze or extract features from the motion flow, and second to integrate those features into patterns of motion (trajectories) that can evoke an appropriate response.Intention is exposed in action.5)The geometry of the vision system facilitates processing.Animals generally have fixed sensor geometries, such as the distribution of receptors in the retina and the projection of their output onto the visual cortex.In advanced vertebrates that use eye movements to scan for detailed information, the sensor geometry is modified to concentrate processing on the target region. This is the fovea of the retina. Peripheral input is compressed and used primarily for detection of new targets, based again on motion.The primate visual system undergoes an approximate log-polar transformation from the photo receptors to the visual cortex. This transformation accomplishes data compression, committing a large part of the cortex to the processing of the central visual field (about 10 degrees visual angle), and a small portion to processing of the peripheral visual field (about 150 degrees on the horizontal). In addition, the transformation facilitates certain analyses of motion that are generally more relevant to an active vision system. For example, auto motion in the direction of the optical axis results in parallel flows on the computational plane.Figure 6 shows the visual receptive fields, and the log-polar projection of the visual sensor employed by the robot in Figure 5.Figure 6.The processing of sensor and motor information is closely related geometrically in the brain. The activation of a sensor field is likely to be associated with the activation of a motor field that controls muscles that further stimulates sensors projection to itsassociated field. An example of this close correspondence is shown in Figure 7 in a sagital section of the human brain.Figure 7.6)Motion information can transform pattern information to achieve perceptualconstancies.Motion can also be used to transform extracted features to maintain alignment of predictions with subsequent observations, greatly reducing computational workload inobject recognition. While motion and pattern are known to be processed in parallel streams through the cortex, the two streams interact at several levels. Figure 8, from DeYoe and VanEssen (1988), summarizes the evidence.The nervous system generally ignores constant input, whether or pattern or motion. Elementary pattern features, such as oriented lines, are most provocative when moving orthogonal to their preferred orientation.1. Stationary features are ignored.2. Oriented lines evoke stronger responses when movingorthogonal to their preferred orientation.3. Secondary and tertiary cortex contain higher percentages of cells that are direction specific.4. Location specificity decreases while direction specificity increases with distance from primary sensory cortex.Figure 8.In the absence of visual input, the process can free run as the transformed features create new motion that leads to new transformations. What happens during a dream? The images move and often undergo unusual transformations. During a dream, eye movements occur (REM sleep) but are poorly organized. The reconstruction of images isa dynamic process, both creating motion and depending upon motion.1. Dream images move on their own.2. Dream images transform rationally and then decompose.3. Vivid dreams are associated with poorly organized eye movements (REM sleep).4. The reconstruction of images in a dream may involve the motion transformation of pattern features and the perception of new motion as a consequence. The process could then free-run.5. Visual input during the waking state can justify motion-pattern interactions (reality testing).7)Visual perception is an active process.Also obvious.The purpose of the central nervous system is not to dream, but to act. This perspective has been available in the neurobiological community at least since the time of Tolman (1932) and is frequently reiterated (Arbib, 1972; Pribram and Carlton, 1984; Roitblat, 1988, 1991; Varela, 1979). Its reciprocal, that the purpose of action is to perceive, is also voiced (Powers, 1973; Bandopadhay et al.,1986; Whitehead and Ballard,1990; Burt, 1988).Experience allows discrimination.Active perception is the application of control strategies to data acquisition based on the current state of data interpretation and the goal or task of the process (Bajcsy, 1988). Active perception occurs during the processes of autonomous sensor-effector control. Active perception is the execution of some behavior that results in the increased probability of encountering a specific stimulus. At a higher level, active perception attempts to satisfy a need for information. It can accomplish this by changing the relative perspective of the organism to its environment. Active perception is a means first to diversify contact with the environment and second to reduce distraction, improve the signal to noise ratio and reduce the computational requirements. Aloimonos et al. (1987) point out that problems that are ill-posed and nonlinear for a passive observer are well posed and linear for an active observer.Uncertainty in the environment is the reason why active perception is required. An uncertain observer is evidenced by random behavior. Non-random behavior in a noisy environment is evidence for the success of active perception.1. The real world contains uncertainty.2. An uncertain agent acts randomly.3. Non-random behavior is evidence for active perception.4. Active perception is the application of experience to data collection.5. Active perception increases the probability of finding a target.6. Active perception reduces noise and computational requirements.8)Reflex saccadic eye movements sample the environment.Once a global search has acquired a target, a more detailed search performed by scanning mechanisms permits a logical sampling of target attributes, whether or not the target is itself moving. Target attributes compete for attention as do multiple targets observed from a distance. Figure 9 shows such a scan path produced by a human observer. The darkest blotches are the saccade target locations where the observer's eyes rested for approximately 0.5 sec prior to moving ballistically on to the next location.Experience is gained through observing the order in the environment (correlations) produced during reflex reorientations to salient features of an object.Figure 9.Smooth pursuit eye movement temporarily maintain the target on the high resolution fovea but are frequently interrupted by small saccades that continue to actively sample the geography of target attributes. The reader may easily verify this for himself by observing a moving automobile at 100 yards. The eyes will smoothly track the automobile, but will also jump from location to location on the body of the automobile to identify salient features.9)Expectations drive search patterns over familiar targets.After a period of observation when data collection is controlled primarily by reflex saccades, the vision system begins to anticipate the next saccade and preempts the reflex. Learned scan paths are the active processes of perception.Rizzo et al. (1987) studied the fixation patterns of two patients with impaired facial recognition and learning and found an increase in the randomness of the scan patterns compared to controls, indicating that the cortex was failing to direct the search for relevant information with a degree of control that exceeded the attractive potential of the stimulus features.Figure 10Yarbus (1967) demonstrated the sensitivity of patterns of eye movements to the cognitive requirements of a visual search task. The regions of an image that were most often visited as a saccade target contained information relevant to the task. Without explicit task requirements, individuals had idiosyncratic scanpaths (Figure 10) suggesting that the sequence of saccades were determined not solely by the stimulus features, but by an interaction of stimulus features and an agenda brought to the task by the individual, that is, the individual demonstrated some expectations about the image to be viewed. Yarbus expressed this finding as "...people who think differently...see differently" (Yarbus, 1967, p. 211).1. Experience allows anticipation of features that can interact with the target features and drive the scan path.2. Learned scan paths are an active process of perception.3. Brain damaged patients with poor face recognition have random scan paths.4. Cognitive requirements (expectations) can influence a scan path.10)Recognition is the verification of a prediction.The verification of a prediction is the amplification of the current input that matches the reafferent activity, this process is similar to template matching or adaptive resonance theory of Carpenter and Grossberg (1987). An output results from an amplified input pattern as associated motor fields are recruited.Recognition is a phase transition that changes the dynamic state of the system. It is not a point process or even a limit cycle, which are both maladaptive and incompatible with survival. The phase transition places the system in a new behavioral context, from which responses are deemed correct or incorrect by other observers.In a study of scan paths and perception of the young woman/old woman ambiguous figure, Gale and Findlay (1983) found that fixation patterns correlated with the perception of the figure. The perception of an old woman (Figure 11) was accompanied by saccades that collected data on the mouth and nose of the figure (a vertical sequence of data acquisition) while the perception of a young woman was accompanied by saccades that collected data on the eye lash and ear (a horizontal data acquisition that missed the critical clues of the old woman in the figure).1. Recognition builds from the accumulation of data that match expectations.2. All high level brain states are normally transient.3. Recognition may undergo a phase transition (hysteresis may be involved) after encountering data that mismatch the current bias.2. The phase transition places the system in a different state with a different bias and different expectations.Figure 11.11)Acquisition and use of information are inseparable processes.In natural vision systems, the acquisition and use of information are not separable processes. Normally, irrelevant objects are ignored or quickly forgotten. Quite abstract two dimensional designs can gain significance for even some invertebrates if the design is correlated with the satisfaction of some vital need of the animal.12)Animals learn environmental correlations to satisfy internal needs.Animals learn not to please us, but to satisfy some internally sensed deficiency, such as hunger, thirst, restraint, sex, etc. The deficiency triggers an increase in neural activity (arousal) which is reduced in the course of satisfaction. This is diagramed in Figure 12.1. Classical or Pavlovian conditioning is the model.2. An internal deficiency is sensed such as hunger, thirst, cold, or pain;3. Arousal is increased followed by activity;4. The object of satisfaction is found followed by decreased arousal and activity.5. Environmental features present during the change in arousal are associated with the sensed event that changed the arousal.6. Thus we experience and anticipate rewards and punishments.Figure 1213)Machines can learn similarly if needs are appropriately defined and tested.While the expected major benefit of using a machine vision system is freedom from the requirement to satisfy vital needs, the mechanisms involved in the acquisition and use of new information by a natural vision system are relevant to the development of analogous processes in an artificial vision system.Motivation is generally ignored in machine learning. The learning process is controlled by an operator who determines when behavior is required, what behavior is required and which events are relevant for recall. In this scenario, the machine is not learning, instead the program parameters are being adjusted "on line". To approximate natural learning, a criterion for behavior must be sensed by the machine. Energy resources have been used (). When energy reserves drop, the activity of the machine is increased, when energy reserves are restored, the activity is reduced. Learning is accomplished in this protocol by correlating the motor output and sensory input present during the changes in activity and energy reserves. Events that lead to increases in activity (due to low energy reserves)are to be avoided, while events that lead to decreases in activity (due to restored energy reserves) are to be approached. This mechanism must allow for hysteresis, for activity itself will decrease reserves.In every adaptive system, natural or synthetic, there are one or more reasons to change its structure and its input-output transfer function. In a supervised system, these reasons are exogenous. In an autonomous system, the reasons are endogenous. In a supervised autonomous system, the exogenous reasons are apparent to the supervisor, but they are effective only if they manipulate endogenous factors.The appropriate selection of adaptation criteria in large part determines the success of adaptation. The mediation of the adaptation criteria is a biphasic process. Active network connections are strengthened when the output of the system contributes to the restoration of the criterion set-point values, and are weakened when it differs from those required values.The experience of an artificial vision system with the types of information with which it must function, mediated by exogenous or endogenous reasons to change, allows the system to self-organize and determine, on its own, the relevant features, both in space and in time, that can be used to discriminate and respond appropriately to dynamic visual input.1. Endogenous Motivation: energy reserves (useful in fielded systems), activity levels (optimize data collection per computational speed).2. Exogenous Motivation: apply by manipulating one of the endogenous reflexes.3. Strengthen associations between sensor fields when homeostatic set-points are approached. Weaken associations upon withdrawal from set-points.4. The analogue of the arousal parameter may be the sensitivity of the perceptual system to phase transition.5. Frequent changes in state with high arousal discourage discrimination learning.14)Machine learning, following biological precedent, requires a reflex base,sensor preprocessing for feature definitions, abstract association matricesbetween sensor domains.All behavior is built upon simple reflexes. One such reflex in shown in Figure 13. All complex behavior is achieved through the modulation of basic reflexes as shown in Figure 14.Motivation is the result of a reflex increase in activity due to an interoceptor signalling some deficiency. The reflex base for behavior has several advantages: it provides self preserving behavioral defaults, it scales learning to the physical limits of the system, it keeps learning relevant, it connects elementary features with elementary motor responses.Figure 13.Figure 14.Sensor preprocessing is a means to analyze input. Elementary features are made available for coding events. Multi-layer neural networks can learn discriminable coding, but at great computation cost. The natural neural system applies plasticity judiciously and not universally. No evidence of long tern plasticity in the spinal cord. Most functions of the brain stem, including the hypothalamus are species specific and innate. The organization of feature analyzers in primary cortex can be impaired with impoverished environments,but normal exposure yields similar results between individuals of a species. It is in the multi-sensory association cortex that neural responses cannot be predicted within a species. "Grandmother" cells apparently do not exist, rather the perception of one's grandmother is a spatial-temporal pattern of activity in larger numbers of cooperating neurons, resulting in the sequencing of multiple muscle groups. No single location in the nervous system contains a specific idea, or makes unilaterally a single decision. The natural neural network is a cooperative venture. Figure 15 shows an example of population coding.Adaptation is correlated with visual capability in nature, and where we want to improve capability in our artificial systems, we should explore the mechanisms of adaptation and incorporate these into our artificial systems.The appropriate motor output of an adaptive polymodal sensor association field follows from the dynamic reconstructions of the elementary sensory fields that accompanied the correct or successful behaviors.1. Reflex base.2. Multiple sensor systems with feature extraction and recomposition hierarchy.3. Association matrices between high level features of different sensor modalities.4. Topographical mapping of sensor features and motor mechanisms - for scan paths, voice production, teletype, etc.Figure 15.15)Neural networks, whether biological or artificial, self organize and selectidiosyncratically relevant features for discrimination andprediction of environmental contingencies.As designers of an artificial visual system, we can specify the decomposition of an image but this does not guarantee that the resulting features will be present in the target and obvious to the machine vision system. We could find that it takes less work to allow the machine itself to determine what is relevant. It could do so by simply selecting the features that make it through its filters at the time the critical decisions are required.In the process of self-organizing to regularities in the environment, desired responses to classes of environmental conditions become probable. Such an increase in the probability in the scan path of a machine vision system with learning is shown in Figure 16.1. It is difficult for the designer to anticipate what is relevant for a learning system.2. Natural and artificial learning systems discover relevant features and correlations from the order in the environment as filtered by the systems experience based predispositions.Figure 16.16)Recommendations and Summary of Progress in machine vision at NRaD The approach we advocate follows biological precedent and incorporates in its functional design low level deterministic specific responses to unspecific stimulus conditions (reflexes), monitored by accessory channels containing specific organizations for input pre-processing and output post-processing coupled by a large loosely differentiated matrix of adaptive processing elements, analogous to neurons or interneurons. The adaptation rules should be based on criteria relevant to the survival of the machine. The gross architecture of the artificial visual processing stages that we have implemented is shown in Figure 17. This architecture was used to learn the scan paths of Figure 16. Long-term adaptations (learning) were permitted only in the association cortex layer.A large literature on both natural and artificial learning systems support this architecture and adaptation mechanism.1. Emulate nature.2. Include neurobiologists in design teams along with computer scientists.3. Avoid historical biases.Figure 17.We have available to date algorithms that emulate natural visual information processing. These algorithms perform 1) visual sensor to processing layer mapping that accomplishes data compression using a log-polar transformation (Blackburn, 1993a), 2) visual motion analysis of local activity in the log-polar domain (Blackburn and Nguyen, 1994b), 3) target acquisition and localization based on segmented motion (Blackburn and Nguyen, 1995), 4) feature analysis and re-synthesis by a hierarchical organization incorporating motion mediated transformations (Blackburn, 1993b), 5) adaptive associations of invariant spatio-temporal features and search behaviors (Blackburn, 1992), 6) cross modal adaptive sensor mapping as in Figure 18 (Blackburn and Nguyen, 1994b). The degree of maturity of these processes is inversely proportional to their order in the list.Figure 18.ReferencesAloimonos, J., Weiss, I. and Bandyopadhyay, A. (1987) Active vision. CAR-TR-317, University of Maryland, Center for Automation ResearchBajcsy, R. (1988) Active perception. Proceedings of the IEEE, 76, 996-1005. Bandopadhay, A., Chandra, C. and Ballard, D.H. (1986) Egomotion using active。
