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点云特征提取 详细 实用 经典的讲述过程及方法(Point Cloud Feature Extraction practical details about the processes and methods of classic)

free image to be used freely

1.本程序主要处理BMP位图。 2.为了方便读者学习，程序各步骤都被拆分开实现了，通过点击相应按钮可以看到每个步骤处理的结果。 3.如果是进行人脸识别，需要先打开一幅位图依次进行“人脸检测与定位”操作和“人脸特征标注”操作，然后再打开需要比较的第二幅位图，也是依次进行所有操作，最后进行识别以区分先后两个人脸。(This procedure deals mainly with BMP Bitmaps. 2. In order for the reader to learn, each step of the program is split and the results of each step can be seen by clicking the appropriate button. 3. In the case of face recognition, it is necessary to open a bitmap for "face detection and location" and "face feature tagging" in turn, then open the second bitmap to be compared, and then perform all the operations in turn, and finally identify to distinguish two faces in succession.)

说明：  基于Matlab的图象处理算法，共有6种处理算法的程序代码，对学习很有帮助，呵呵。(based on Matlab image processing algorithm, a total of six types of processing algorithm code, to learn helpful, huh.)

自己开发的一种点云降噪方法，可以去除物体主体之外的部分的点云数据（物体点云数据为三维扫描仪获得）(A point cloud noise reduction method developed by ourselves can remove part of the cloud data outside the main body of the object (object cloud data is obtained for a three-dimensional scanner))

本书叙述如何使用Python中的OpenCV库实现视频捕捉、图像处理、目标检测等功能。(This book will show you how to use OpenCV s Python bindings to capture video, manipulate images, and track objects with either a normal webcam or a specialized depth sensor, such as the Microsoft Kinect.)

对监控视频中的目标进行识别，提取背景信息(The target in the surveillance video is identified and background information is extracted)

本工程实现了二维空间点的关于任意点的对称与关于任意直线的对称。(This project realizes the symmetry of arbitrary point and the symmetry of arbitrary line in two-dimensional space.)

利用GS算法实现相位的校正，从而使相位得到一定程度的改善(The phase correction is realized by GS algorithm, so that the phase is improved to a certain extent.)

We extend the well-known Shi-Tomasi-Kanade tracker by introducing an automatic scheme for rejecting spurious features. We employ a simple and efficient outlier rejection rule, called X84. Experiments with real and synthetic images confirm that our algorithm makes good features to track better