Description: 非常详细的高精度碰撞检测代码，精确到三角形、边、点，优化过滑动时的碰撞检测，完全没有震动现象。代码中把三角形等元素具体成类参与计算的方法很有参考价值。
代码内含3d向量计算函数，在ogengl、d3d下均可运行。-Very detailed high-precision collision detection code, accurate to the triangle, edge, point, when optimized sliding collision detection, there is no vibration phenomenon. Code elements such as the triangle into a specific type of calculation is very involved in reference value. Code containing the 3d vector calculation function, in ogengl, d3d may run under. Platform: |
Size: 441344 |
Author:sking |
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Description: 欢迎视觉革命。在微软的Kinec带领下，您现在可以使用三维计算机视觉技术建立数字化三维模型，人和物体，你可以用手势和语音指令操作。这手势指导，提供所有的技术和概念的信息，你需要为Kinect建立出色应用，使用的加工编程语言和Arduino的微控制器。
无论你是学生，业余爱好者，制造商，玩家，或硬件黑客，Ｔｈｉｎｇｓ Ｓｅｅ让你与几个Kinect的项目运行，给予你用这神奇的三维计算机视觉技术建立你自己的玩意和创意项目的技能和经验。解锁你的能力，建立与Kinect的交互式应用程序。
了解面部识别，步态分析和深度成像
分析和操作点云
用骨架和姿势检测，跟踪检测对象，使用ｂｌｏｃｋ ｔｒａｃｊｉｎｇ 检测物体
使用手势接口作为辅助技术
为设计和制造创建模型，使用三维扫描技术和三维打印机钻研动物和动画的运动跟踪
在这本书中用廉价的现成组件构建书里的每一个项目.-Welcome to the Vision Revolution. With Microsoft’s Kinect leading the way, you can now use 3D computer vision technology to build digital 3D models of people and objects that you can manipulate with gestures and spoken commands. This hands-on guide provides all the technical and conceptual information you need to build cool applications for Kinect, using the Processing programming language and the Arduino microcontroller.
Whether you’re a student, hobbyist, maker, gamer, or hardware hacker, Making Things See gets you running with several Kinect projects, and gives you the skills and experience you need to build your own fun and creative projects with this magical 3D computer vision technology. Unlock your ability to build interactive applications with Kinect.
Learn about face recognition, gait analysis, and depth imaging
Analyze and manipulate point clouds
Track people with skeletonization and pose detection, and use blob tracking to detect objects
Use gestural interfaces f Platform: |
Size: 12392448 |
Author:hjm |
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Description: 地面激光扫描（TLS，也称为地基光探测和测距，激光雷达），能高精度，详细的3D模型，测量自然的环境提供有效的数据采集方法。然而，尽管高密度和质量，数据本身的，所获得的数据中含有所需的进一步建模和分析没有直接情报 - 仅3D几何图形（XYZ），3分量颜色（RGB），而激光返回的信号强度（I）中的每个点。-Terrestrial laser scanning (TLS, also called ground based Light Detection and Ranging, LIDAR) is an effective data acquisition method capable of high precision, detailed 3D models for surveying natural environments. However, despite the high density, and quality, of the data itself, the data acquired contains no direct intelligence necessary for further modeling and analysis- merely the 3D geometry (XYZ), 3-component color (RGB), and laser return signal strength (I) for each point. Platform: |
Size: 29696 |
Author:周保兴 |
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Description: 用于图像特征提取和匹配，三维重建等的经典方法，包括sift，surf，Harris，RANSAC,8点算法等-For image feature extraction and matching, 3D reconstruction and other classical methods, including sift, surf, Harris, RANSAC, 8 point algorithm, etc. Platform: |
Size: 9069568 |
Author:陈美美 |
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Description: Multispectral remotely sensing imagery with high
spatial resolution, such as QuickBird, IKONOS satellite
imagery or Aerial imagery, especially in urban scenes, often
perform spectral variations and rich details within a category,
resulting in a poor accuracy of classification. To seek an efficient
solution, this paper presents a non-parametric and variational
multiple level set model by a joint use of Aerial image and two
products, digital terrain model (DTM) and digital surface model
(DSM), directly or indirectly derived raw LiDAR (Light
Detection And Ranging) 3D point cloud data. Proposed model is
to minimize an energy function. The energy includes two terms.
First term is mainly image-based energy which introduces Parzen
Window density estimation technique in the multiple level set
framework. To make up the disadvantages-Multispectral remotely sensing imagery with high
spatial resolution, such as QuickBird, IKONOS satellite
imagery or Aerial imagery, especially in urban scenes, often
perform spectral variations and rich details within a category,
resulting in a poor accuracy of classification. To seek an efficient
solution, this paper presents a non-parametric and variational
multiple level set model by a joint use of Aerial image and two
products, digital terrain model (DTM) and digital surface model
(DSM), directly or indirectly derived raw LiDAR (Light
Detection And Ranging) 3D point cloud data. Proposed model is
to minimize an energy function. The energy includes two terms.
First term is mainly image-based energy which introduces Parzen
Window density estimation technique in the multiple level set
framework. To make up the disadvantages Platform: |
Size: 2544640 |
Author:yangs |
Hits:
Search - 3d point detection