kinect三维重建

基于Kinect-OpenNI-OpenCV-OpenGL的环境三维重构项目源码详见：/forum/viewtopic.php?f=1&t=13042前几天刚入手了期待已久的Kinect ，用于实验室机器人项目的视觉导航与环境理解。

首先要做的是破解-->连接PC-->获取深度数据和图像数据-->三维点云显示这么几项基本工作。

开始仿照的是饮水思源[1]博客的方法（使用VS2008在windows平台上试用Kinect[2]），利用CL-NUI-Platform 来破解，它的最新版是1.0.0.1210，但我在XP上用会当机，后来换1.0.0.1121 版的就可以用了。

CL NUI 提供了十分简便易用的接口，在OpenCV 上调用很简单，另外它还提供了Kinect 底座马达的控制接口和LED 灯颜色的选择接口，其例程中可以操控Kinect 上下摆动。

如果只需要获取深度数据和图像数据，CL NUI 就够用了。

不过要做深入的应用，比如人体姿态识别、骨架提取、深度数据与图像数据的合并等等，就该用到OpenNI 了。

国的CNKINECT[3]是个不错的Kinect 开发论坛，版块丰富，有很多资料可供借鉴。

我通过论坛介绍的方法[4]成功配置了OpenNI + Kinect，先是用最新版的OpenNI+SensorKinect+NITE ，但在XP 下不能正常运行，可能跟 .net 平台有关，老实按上面论坛的方法装就成功了。

另外用CMake + VS2008 装了最新的OpenCV_SVN，开始试过在CMake 里选择With TBB，但诡异的是TBB 似乎只适用于VS2005，在VS2008 编译后试用里面的samples 老是提示报错找不到msvcp80.dll，重新用CMake 配置取消了With TBB，就一切正常了。

[编辑]一、深度摄像机的视角调整与深度/彩色图像的合并通过研究OpenCV_SVN 与OpenNI 相关的代码（cap_openni.cpp）发现，OpenCV 目前只支持对Kinect的深度图、视差图和彩色/灰度图及相关属性的读取，更进一步的设置还没有实现。

基于Kinect与PCL的三维重建系统研究的开题报告一、研究背景和意义随着虚拟现实、增强现实技术等新兴技术不断发展，三维重建技术也逐渐成为研究热点。

在工业、文化遗产保护、医学等领域，三维重建技术具有广泛的应用前景。

传统的三维重建技术主要基于摄像机、激光雷达等主流设备，但这些设备昂贵、操作复杂，且在室内场景中容易受到光线的影响。

相比之下，基于Kinect和PCL库的三维重建技术更加便捷、快速、精确。

因此，本研究将探讨基于Kinect和PCL的三维重建技术，并将其应用于实际场景中。

二、研究内容和方法本研究将主要分为以下几个部分：1. 系统搭建和环境配置：在搭建三维重建系统前，需要对Kinect和PCL库进行环境配置。

本研究将详细介绍Kinect和PCL库的安装和配置方法。

2. 数据采集与处理：本研究将使用Kinect采集实际场景三维数据，并使用PCL库进行处理。

首先，需要对数据进行滤波处理和信号增强，提高数据的精度和稳定性。

然后，对数据进行配准和重建，生成三维重建模型。

3. 算法优化和实现：本研究将对PCL库中的基本三维重建算法进行分析和优化，力求提高算法效率和重建精度。

然后，将算法实现到三维重建系统中，实现实时三维重建。

4. 系统测试和评价：最后，本研究将对三维重建系统进行测试和评价，以验证其重建精度、效率和可靠性。

三、研究预期成果本研究期望得到以下预期成果：1. 基于Kinect和PCL库的三维重建系统：实现基于Kinect和PCL的三维重建系统，并提供用户友好的界面。

2. 三维重建算法优化：通过分析和优化PCL库中的基本三维重建算法，提高算法效率和重建精度。

3. 实际场景数据重建：使用系统生成三维模型对实际场景进行重建，并进行评估和分析。

四、研究计划研究计划如下：1. 第一阶段（2022年6月至2022年9月）：系统搭建和环境配置。

学习Kinect和PCL库的基本原理和库函数，完成环境配置。

2. 第二阶段（2022年9月至2023年3月）：数据采集与处理。

基于Kinect的动态人体三维重建的开题报告一、选题背景随着虚拟现实技术的不断发展，动态人体三维重建的需求也越来越大。

这种技术可以应用于游戏、电影等领域，能够实现真实逼真的人体动态效果。

目前，基于Kinect的动态人体三维重建技术已经比较成熟，但是仍然存在一些问题，如精度不高、容易受到环境因素的影响等。

因此，本文将从这些问题出发，研究如何提高基于Kinect的动态人体三维重建的精度和可靠性。

二、研究内容1. 研究基于Kinect的动态人体三维重建的原理和技术路线；2. 分析当前基于Kinect的动态人体三维重建存在的问题；3. 探索如何提高基于Kinect的动态人体三维重建的精度和可靠性，包括优化算法、增强环境稳定性等；4. 设计实验并进行验证，评估提出的方法的有效性和可行性；5. 结合实际应用场景，综合考虑Kinect设备的性能、场景复杂度等因素，提出应对不同场景下的动态人体三维重建技术方案。

三、研究意义本研究的成果不仅可以提高基于Kinect的动态人体三维重建的应用价值，还可以为其他相关领域的研究提供思路和方法，如虚拟试衣、医学影像等。

此外，本研究也有助于探索虚拟现实技术的应用前景和发展方向。

四、研究方法和技术路线本研究主要采用实验室实验和实际场景测试相结合的方法。

具体的技术路线如下：1. 建立基于Kinect的动态人体三维重建的数学模型和算法；2. 使用Kinect设备采集动态人体图像序列，并对图像序列进行预处理和实时处理；3. 基于已有算法提取肢体关节点、重建人体骨架、生成人体模型；4. 优化算法，提高重建的精度和稳定性；5. 构建实验场景，进行实验验证；6. 对实验结果进行分析和评估；7. 对提出的方法进行应用场景测试并给出方案。

五、预期结果本研究旨在提高基于Kinect的动态人体三维重建的精度和可靠性。

预期可以实现以下结果：1. 实现基于Kinect的动态人体三维重建，达到一定的精度要求；2. 提出优化方案，使得重建的精度和稳定性更好；3. 探索应对不同场景下的动态人体三维重建技术方案。

Kinect实现简单的三维重建Kinect实现简单的三维重建标签：Kinect三维重建OpenFrameworks2013-03-29 13:028418人阅读评论(71)收藏举报分类：Kinect（1）OpenFrameworks（3）版权声明：本文为博主原创文章，未经博主允许不得转载。

Kinect想必大家已经很熟悉了，最近基于Kinect的创意应用更是呈井喷状态啊！看到很多国外大牛用Kinect做三维重建，其中最著名的要数来自微软研究院的Kinect Fusion了，可以看看下面这个视频/show/7q2Sa__pa4-rWcAVtB3Xuw...html，或者/v_show/id_XNDcxOTg3MzUy.html。

可惜Kinect Fusion是不开源的，不过PCL实现了一个差不多的开源版本，/。

有兴趣同时电脑配置高的朋友可以研究一下。

最近比较闲，有一点手痒，想自己做一个三维重建，不过肯定不会像Kinect Fusion那么强大，只是自己练练手、玩玩而已。

代码在最后有下载。

1. 获取Kinect深度图：首先我使用微软官方的Kinect SDK来控制Kinect，三维绘图我选用了OpenFrameworks。

OpenFrameworks（以后简称OF）是一个开源的公共基础库，将很多常用的库统一到了一起，比如OpenGL，OpenCV，Boost等等，而且有大量的第三方扩展库，使用非常方便。

具体可见/。

在一切开始之前，我们需要对OpenGL和三维场景做一些设置：[cpp] view plaincopyvoid testApp::setup(){ //Do some environment settings. ofSetVerticalSync(true); ofSetWindowShape(640,480); ofBackground(0,0,0); //Turn on depth test for OpenGL.glEnable(GL_DEPTH_TEST);glDepthFunc(GL_LEQUAL);glShadeModel(GL_SMOOTH); //Put a camera in the scene. m_camera.setDistance(3);m_camera.setNearClip(0.1f); //Turn on the light. m_light.enable(); //Allocate memory to store point cloud and normals.m_cloud_map.Resize(DEPTH_IMAGE_WIDTH,DEPTH_I MAGE_HEIGHT);m_normal_map.Resize(DEPTH_IMAGE_WIDTH,DEPTH_I MAGE_HEIGHT); //Initialize Kinect.InitNui(); }OF是使用OpenGL进行绘图的，所以可以直接使用OpenGL 中的函数（以gl开头），为了方便，OF还自己封装了一些常用函数（以of开头）。

基于Kinect的室内场景三维重建共3篇基于Kinect的室内场景三维重建1随着科技的不断发展，人工智能、计算机视觉等领域正在逐步改变人们的生活方式和工作方式。

在这些技术中，Kinect作为一种能够实现深度感知、人体识别等功能的传感器，其应用领域也越来越广泛。

其中，基于Kinect的室内场景三维重建技术，成为了近年来备受关注的研究方向之一。

一、Kinect技术概述Kinect是由微软公司开发的一个结合了摄像头、深度感知器和麦克风的设备，通过人体轮廓的捕捉和分析，实现人体动作捕捉等各种应用。

Kinect可以通过红外光点的反射、深度感应的计算等技术，将人体的各种动作准确地捕捉到计算机中，并将其转化为计算机能够识别和处理的数据。

二、室内场景三维重建技术室内场景三维重建技术利用计算机视觉技术和三维重建算法，将室内场景或对象的图像和数据转化为三维建模，进而实现对室内场景或对象的快速、精确的重建、分析和数字化。

基于Kinect技术的室内场景三维重建技术，利用Kinect设备可以实时获取场景中的深度图像等数据，并通过循环设备测距算法将这些数据转换为三维坐标信息。

然后，根据这些坐标信息，可通过三维重建算法，对室内场景进行建模和重建。

三、基于Kinect的室内场景三维重建的应用1. 建筑物侦查利用Kinect设备，可快速捕捉建筑物内部空间的三维模型信息，对现场进行快速、准确的测量和分析，为建筑物改建、翻新和维护提供重要的数据支持。

2. 教育仿真基于Kinect的室内场景三维重建技术，可用于创建虚拟实验室、仿真实验场景、虚拟教学交互等，为学生提供更加生动、直观、互动的学习体验。

3. 游戏开发基于Kinect的室内场景三维重建技术，可用于游戏场景的建模与重建，在游戏中创造更加真实、生动的虚拟世界，提高玩家的游戏体验。

四、基于Kinect的室内场景三维重建技术存在的问题及解决方案1. 对环境的要求高Kinect设备对环境要求较高，对灯光、噪声、阴影等都有严格的限制。

基于Kinect的三维场景重建研究的开题报告一、研究背景随着计算机图形学、数字图像处理、立体视觉等技术的不断发展，三维场景重建技术应用越来越广泛。

已经广泛用于建筑测量、室内设计、工业设计、影视制作、虚拟现实等领域。

但传统的三维重建技术需要特定的硬件设备，例如激光雷达、摄像机等，成本较高。

而基于Kinect深度摄像头的三维场景重建技术具有成本低、精度高、控制方便等优点，越来越受到研究者的重视。

二、研究目的本文旨在开发一种基于Kinect深度摄像头的三维场景重建技术，并提出一种有效的算法用于获取三维点云数据，并进行场景重建，以实现高效、准确的三维建模。

三、研究内容1.调研已有的三维重建技术和Kinect相关技术，分析它们的优缺点。

2.设计并实现基于Kinect的三维场景重建系统，包括深度图像获取、点云数据获取、数据处理和三维场景重建。

3.提出一种基于点云数据的三维建模算法，解决点云数据的无序性和噪声问题，并实现场景的可视化重建。

4.验证系统的可行性和效果，并进行实验比较。

四、研究意义本文的研究可以为基于Kinect的三维场景重建技术的发展提供一定的参考和帮助，提供一种低成本、高精度的三维重建解决方案，对相关产业的发展和应用也有着重要的促进作用。

五、研究方法和技术路线本文采用了文献研究、实验研究、数值模拟等方法，采用C#语言、OpenCV、PCL等工具，设计了基于Kinect深度摄像头的三维场景重建系统，提出了基于点云数据的三维建模算法，并在实验中对系统进行了验证和比较。

六、预期成果预期完成一份论文，能够阐述基于Kinect的三维场景重建技术的研究内容、研究方法、实现过程和效果验证。

同时，还将提供基于该技术的三维重建系统软件，实现三维场景重建功能。

七、进度安排第一季度：调研已有的三维重建技术和Kinect相关技术，梳理方法和技术路线，初步设计三维场景重建系统。

第二季度：设计并实现基于Kinect的三维场景重建系统，包括深度图像获取、点云数据获取、数据处理和三维场景重建。

kinect fusion算法摘要：1.引言2.Kinect Fusion算法概述3.算法原理3.1 点云处理3.2 表面重建3.3 优化与可视化4.应用领域5.算法优缺点6.总结正文：【引言】在计算机视觉和增强现实领域，Kinect Fusion算法独树一帜。

它通过将多个Kinect传感器采集的数据进行融合，实现对场景的实时三维重建。

本文将对Kinect Fusion算法进行详细解析，带你领略其魅力所在。

【Kinect Fusion算法概述】Kinect Fusion算法是一种基于Kinect传感器的三维重建技术。

它通过实时捕捉场景中的深度信息和彩色信息，对场景进行三维重建。

与其他三维重建方法相比，Kinect Fusion算法具有更高的实时性和准确性。

【算法原理】Kinect Fusion算法主要包括以下三个部分：【3.1 点云处理】Kinect传感器捕捉到的深度数据是连续的深度值，需要将这些深度值转化为点云数据。

点云数据是由一系列三维坐标点组成的数据集，能更好地反映场景中的物体形状和位置信息。

【3.2 表面重建】在得到点云数据后，需要对点云数据进行表面重建。

表面重建的目的是从点云数据中提取出物体的表面信息，以便后续处理。

常用的表面重建方法有Poisson表面重建、球形重建等。

【3.3 优化与可视化】表面重建完成后，需要对结果进行优化和可视化。

优化主要包括降噪、平滑等处理，以提高表面质量。

可视化则是将重建结果以直观的方式展示出来，便于用户观察和分析。

【应用领域】Kinect Fusion算法在许多领域都有广泛应用，如虚拟现实、增强现实、机器人导航等。

通过实时三维重建，Kinect Fusion算法为这些领域提供了强大的技术支持。

【算法优缺点】Kinect Fusion算法具有以下优点：1.实时性：能够实时捕捉场景信息并进行三维重建。

2.准确性：与其他三维重建方法相比，Kinect Fusion算法具有较高的准确性。

2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)A Brief Talk on the 3D Scanning Reconstruction Program Based onKinect and its ApplicationWang Yongsheng1, a, Zhang Qizhi2, b,* and Liu Xiao2, c1 School of art and design, Lanzhou Jiaotong University, Lanzhou 730070, China2 School of art and design, Lanzhou Jiaotong University, Lanzhou 730070, Chinaa**************,b**********************,c***************Abstract: By combining the Kinect (a somatosensory device) with a supporter and a rotary wheel and using a 3D scanning software named KScan3D to realize a quick scan of the human body, this paper constructs two scanning systems, one of which is equipped with a handheld single-camera comparing to the other adopting multiple fixed cameras, so as to generate virtual 3D models and provide various applications, such as printing 3D objects, generating web pages or making animations and virtual exhibition models.Keywords: 3D scanning restructure; painted sculptures of Dunhuang; digitalization.1. IntroductionThe rapid growth of computer sciences and digital VR techniques has made it possible for using 3D scanning and printing technologies to realize digital 3D visual reconstruction. Such advancement has bee promptly applied to various areas including construction, medical care, archeology and industrial use. Compared to traditional modeling methods, 3D scanning and printing technologies are faster and more precise. Due to a wide range of utilities, human body modeling has become a desperately urgent need.2. 3D Scanning ReconstructionAs described during the experiment in this paper, data are first obtained through Kinect, a somatosensory camera sensor. Subsequently, the data are converted to a 3D mesh by using a software called Kscan3D. A mesh with 360 degree coverage can be achieved based on data showing different angles with the help of Kscan3D, which is capable of automatically capture and organize the 3D grip. Deleting unnecessary point from the data can smooth the data before the final combining and compositing to generate a complete model.2.1 Hardware Construction2.1.1Hardware ConstructionThis system is designed to scan people standing about 1.6 to 1.9 meters tall, which means the supporter needs to be 2.5 meters high at the same level with the Kinect. Each Kinect is set about 64cm away from the other and is responsible for scanning a part of the body. Then it is the software’s job to connect the separated scanning results. The Kinect on the highest position scans the head and shoulders, while the second is in charge of the arms. Similarly, the third shoots the waist and the forth scans the legs and the feet. If this person is short, 3 Kinects may be enough, using the first Kinect for scanning the head and shoulders, the second for arms and waist, and the third for legs and feet. This experiment is conducted by using 3 Kinects. Besides, a rotary wheel running at a uniform velocity is required and its loading capacity has to be adequate to supporting a person for full 360 degree scanning. The rotary wheel is 66cm away from the aluminum supporter as shown in Figure 1.Fig. 12.1.2 What is Kinect and how does it work:Kinect is a somatosensory camera sensor, providing multiple features, for instance, motion capture, image recognition, microphone input and voice recognition. Players are enabled to interact with virtual objects and other players in game as well as to share pictures and information with other XBOX users via internet. Kinect is first designed as a peripheral input equipment for the Xbox and later on Kinect for windows is developed for connecting with PC.How does Kinect work: Kinect is a combination of various sensors, which comprises a color camera,a pair of depth cameras (one is used to emit infrared ray, the other is to received the returned ray), an array of microphones and a motor base, Kinect is able to work within a range from 1.2 m to 3.5 m. Asof Kinect for Windows, the range of the camera is shortened to 40 cm to 3 m.The depth camera uses IR to obtain the depth value of each point corresponding to the image returned (the depth value is actually the distance from the object to the Kinect in mm with 5mm tolerance). The MIC array is actually a microphone arranged horizontally. Due to the gap, it can be used to determine where the speaker is and can reduce noises.First of all, the program has to detect the connected Kinect for initialization. Second, the program is required to configure and enable its desired data flow, i.e. the expected data, including color information, depth data, bone data flow and IR data stream. Next, the corresponding data flow is obtained in accordance with the previous setup. Finally, it is to stop the Kinect and release PC resources.2.1.3 Precautions about the scanned objectOn selecting an object for scanning, it is the first thing to do to think over its features, such as its size, shape, weight and surface material. Sensors of Kscan3D and Kinect/Xtion are capable of scanning a lot of objects, for example, human body, furniture, house or even bigger stuff. Due to the resolution limit, distance from the senor to the object is not supposed to be less than 40 cm and the scanned object not smaller than a grown man's shoe. Objects that are too thin may not have satisfactory scanning results. Generally speaking, the best object to be scanned should be in neutral colors with matte opaque materials. It is hard to scan things of surface materials that are whether dark, reflective, transparent or translucent. Therefore, preparations should be made before scanning. Environmental factors, including air, lights and movements, determine the success or failure of the experiment to a large extent. As of a physical object, it's a must to take its size into consideration and find a way to cover all the angles. For a small and light object, object is placed on the rotary wheel for scanning, while sensors are fixed. In general, the ambient light should cover all directions. As a matter of fact, sunlight may affect the working of IR sensors. It is not easy for scanning under sunlight. Therefore, if necessary, the scanning work is suggested to be done outside in a cloudy weather or be accomplished inside. During the scanning process, it is important to ensure the person or object motionless because movements may lead to a data acquisition failure.2.2Software IntroductionKScan3D is a 3D scanning software utilizing Kinect or Xtion to acquire point cloud data in a real-time manner, which allows multiple depth cameras to work simultaneously for scanning real objects and supports quick generating of complete 3D models.2.3Integration Solution to the 3D Scanning SystemThere are mainly two types of 3D scanning solutions. One is a handheld scanning system with a single camera, while the other adopts multiple fixed cameras.2.3.1 Handheld single-camera scanning systemScanning modes for the handheld single-camera scanning system: the single-camera system has two scanning modes, which are individual scanning and batch scanning.(1)Make sure the box of "enable batch scanning" within the scanning pane is not checked;(2)Set up an initial delay (seconds);(3)Turn the sensors towards the object and ensure the object can be seen from the real-time video feedback;(4)Click the SCAN buttonFigure 2 shows the scanning results.Fig. 2Batch scanning:(1)Check the box of "enable batch scanning" within the scanning pane;(2)Select the number of objects to be scanned(3)Set up a time delay between two scans(4)Set up an initial delay (seconds);(5)Turn the sensors towards the object and ensure the object can be seen from the real-time video feedback;(6)Click the SCAN buttonFigure 3 shows the scanning results.Fig. 32.3.2Fixed multiple-cameras system1. Start the KScan3D software and make sure all sensor are working, as shown in Figure 4.Fig. 42.Adjust the position of the sensorIf needed, it is Ok to move up or move down the position of the sensor in the list until the live response sequence complies with the sensor's actual position, as shown in Figure 5.Fig. 53. Capture an individual scan.Correctly set up the scanning options without checking the option for batch scanning. Adjust the parts to be scanned to the corresponding position and delete until the end, as shown in Figure 6 and Figure 7.Fig.6Fig.74. Capture a full-body scan（1）Capture a full-body scan. Set up to the Capture Only mode and check the box of batch scanning with the number of scans set to 40. The person should stand in the middle of the rotary wheel. Start the wheel before clicking the scan button as shown in Figure 8 and Figure 9.Fig. 8Fig.9（2）Click the mesh-editing button and select the first picture. Press ctrl+a to select all thumbnails. Click the Point Cloud panel to set up the alignment as shown in Figure 10.Fig.10（3）Click the Build (for compositing) button and Kscan3D can turn each point into a mesh. In the end, delete unnecessary data. Using the basic mesh editing functions can help complete and export a high-quality result.Fig.11（4）Click the Finalize (finish) button to get the final model. Select the Finalize button for a combined mesh. Combination is required to be completed before export. The three properties in the finish step are used to adjust parameters like mesh density, inner fill and decimation, as shown in Figure 12.Fig.122.4 As long as the model is generated, select the Export button to export the mesh or point cloud to the current file. KScan3D can export the following file formats: fbx, obj, ply, stl, asc and 3d3. （1）Select a format as shown in Figure 13Figure 13（2）Export dataIn the control panel, load the mesh or point cloud to be exported. Please note that combine mesh is not supported for export. Click the Export button on the tool bar and an interface of folder selection will pop up as shown in Figure 14.Fig. 14Select a specified folder or create a new folder to store the mesh or pint cloud as shown in Figure 15.Fig. 153. 3D printoutsTechnical support: 3D printing is a form of fast manufacturing technology. By "slicing" the drawing of the object to print into numerous layers, the processor heats up and presses the filament PLA (a new type of biodegradable material as the raw material) by utilizing the fuses deposition molding technology (FDM) to process each layer under computer control so as to get the formed 3D object. This is the most commonly adopted 3D printing method featuring high technical maturity and low cost.Working steps of a 3D printer: use Kinect to scan the model and set up the printing parameters with the built-in software. Import the stl file from the memory card to the printer for printing. This paper uses a 3DA8 industrial printer manufactured by JGAURORA, which is able to print a maximum size of 350*250*300mm. The printing of large objects can be done through splicing. Coloring can be completed through spraying or manual painting.Models created during this experiment are shown in Figure 16, Figure 17and Figure 18.Fig.16Fig.17Fig.184. Online interaction demoBlender is a virtualization engine for fast modeling, which is often used by modeling for games. As an open-source WebGL framework, Blend4Web can be used to create interactive webpages. Without going out, a user can have the chance to view 3D human models on webpages, check for details by rotating angles or zooming and share it to other users. This is impossible to realize by traditional browsing methods.Through the Blender4web plugin, the scanned and finished human body model is allowed to be directly exported to a .html file. The Blender4web export mode is not included in the Blender so we have to manually install it: first, download the add-on corresponding to the Blender version from the official website for bledner4web. Then, in the Blender, click File->User Preferences->File-> scrips->the zip containing the bledner4web add-on-> ->Save User Settings. Next, exit the blend and open File->User Preferences->Addons->import-export->Blend4web. After that, the .html option can be seen in the File->Export. Figure 19shows an exported webpage.Fig.195. Applied to animation and virtual exhibitionUsing the 3D scanning technology to conduct a comprehensive human body scan, a 3D model of human body and materials can be obtained. With parameter adjustment to enrich the changes and combinations, once these color models are inputted into 3D animation software like 3dsmax, fast, accurate and vivid performance can be achieved as well as virtual exhibition, which has greatly boosted the diversified development of the animation industry.6. Conclusion3D scanning and printing technologies have made it possible to express human models in a perfect, accurate and quick manner by inputting the scanned 3D information into a computer. This paper utilizes two scanning methods for human body modeling and studies their feasibility by printing a human model. However, due to scanning angles, the model may have flaws affecting the accuracy of modeling, which need to be improved in the future.References[1]System of Online Fitting Room Based on Web [J], Yang Wenwen, Guo Jianan and Yang Xiaodong, Computer Era, 2015, 5[2]Application of 3D Scanning and Printing Technologies to the Repair of Crack Decorative Components [A], Jiang Yueju, Lv Haijun, Yang Xiaoyi, Xu Wei and Ma Xing Sheng, Construction Technology, 2016,12[3]Research on the 3D Scanning and Printing of Human Head [A], Song Junfeng, Shenyang University of Technology, 2016[4]Development of the 3D Printing Technology and its Software Implementation [J], Shi Yusheng, Zhang Chaobai, Bai Yu and Zhao Zuye, Science China Information, 2015[5]Present Research on the 3D Printing Technology and Critical Know-Hows [J], Journal of Material Engineering, Zhang Xuejun, Tang Siyi, Zhao Hengyue, Guo Shaoging, Li Neng, Sun Bingbing and Chen Bingqing, 2016, 2[6]Research on the Technology and Working Principle of Kinect [J], Shi Manyin, Natural science journal of Harbin Normal University, 2013, 6。

kinectfusion算法详解KinectFusion算法是一种利用微软Kinect传感器进行三维重建的技术。

它能够实时地将物体或环境的三维形状转化为点云数据，从而实现对实时场景的三维建模。

本文将对KinectFusion算法进行详细解析，包括算法原理、实现步骤以及应用场景等方面。

我们来看一下KinectFusion算法的原理。

该算法主要依赖于Kinect传感器提供的深度图像和彩色图像。

深度图像是通过红外光和红外摄像头测量物体与Kinect传感器之间的距离而得到的。

而彩色图像则是通过普通的RGB摄像头获取的。

基于这两个输入，KinectFusion算法能够实时地生成环境中物体的三维模型。

KinectFusion算法的实现步骤如下：1. 初始化：首先，需要将深度图像和彩色图像进行配准，以保证它们的空间对齐。

这一步骤通常需要使用传感器提供的内置标定参数。

2. 预处理：在进行三维重建之前，需要对深度图像进行预处理。

这包括去除噪声、填充空洞等操作，以提高后续处理的准确性和稳定性。

3. 三维重建：在预处理完成后，可以开始进行三维重建。

首先，需要根据深度图像和内置标定参数计算相机的内外参数。

然后，将深度图像转化为点云数据，并将其与彩色图像进行配准。

最后，利用体素格网（Voxel Grid）等方法将点云数据进行三维重建，生成物体的三维模型。

4. 实时更新：一旦生成了初始的三维模型，KinectFusion算法可以实时地将新的深度图像与已有的模型进行融合。

这样，即使物体在移动或者场景发生变化，也能够及时地更新模型，保持模型的准确性和完整性。

KinectFusion算法在虚拟现实、增强现实等领域具有广泛的应用。

例如，在虚拟现实游戏中，可以利用该算法实时地将玩家的动作转化为三维模型，实现身临其境的游戏体验。

在医学领域，可以利用该算法进行手术模拟和病灶分析等工作。

此外，KinectFusion算法还可以应用于室内导航、机器人感知等领域，为相关应用提供三维环境模型。