计算机视觉课程1.ppt

1、,Teacher: Prof. Liu Yuncai,计算机视觉课程COMPUTER VISION,Reference books: 1. Machine Vision, by Ramerh Jian, et al (Major Reference) 2. Computer Vision, by Dama H. Ballard, et al. 3. Vision, By David Marr. 4. Introductory Techniques for 3-D Computer Vision, by Emanuele Trucco. 5. Computer Vision and Image

2、Processing, by Scatt E.Umbaugh. 6. Algorithm for Image Processing and Computer Vision, by J.R.Parker. 7. 机器视觉，贾云得 编著 8.计算机视觉的理论和实践， 李介谷著 9 . 计算机视觉计算机理论与算法基础， 马颂德,Rule of grading: Homework: 10% Examination:60% Project:30% Important Deadlines: Hand in project proposal: May 11, 2010 Hand in project rep

3、ort: July 6, 2010 All written in Chinese (中文书写) Final Examination: July 6, 2010,Course 1Introduction,Course 1Introduction,1.What is Computer Vision Computer vision aims to recover useful information about a (3D) scene from its 2D projections (images). 3D depth / 3D structure 3D motion analysis 3D su

4、rfaces and orientation status of 3D objects, so on meaning of actions of 3D objects (cognition),Every task is tough since it is to be understood from flat images!Computer vision is also called as : Machine visionRobot visionImage understandingScene analysis (in early years),课程内容：1) 绪论 (Introduction)

5、2) 图象滤波 (Image Filtering)3) 二进制图象处理 (Binary Image Processing)4) 区域 (Region)5) 边缘检测 (Edge Detection)6) 立体视觉 (Stereo)7) 运动的理解与估值 (Motion)8) 轮廓 (Contours)9) 纹理 (Texture) 10) 图象光度学 (Shading)11) 光流场 (Optic Flows)12) 系统校准 (Calibration)13) 曲线与曲面 (Curves and Surfaces)14) 动态视觉 (Dynamic Vision)15) 三维识别 (Objec

6、t Recognition),2. Related fields image processing computer vision pattern recognition artificial Intelligence neural network psychophysics,3. Perspective Projection pin-hole camera model,projection center (i.e., camera) is at the origin of scene coordinate system with optic axis of camera pointing t

7、o z-axis direction of coordinates origin of image coordinate system is located at (0, 0, f) of scene coordinate system (f is focus length of the camera), the X- and Y-axes of image coordinates are parallel with x- and y- axes of scene coordinates, respectively camera does not have any lens distortio

8、ns.,z,(1) Image point,Image Line 3D line l is projected onto image plane through projecting plane to get image line L:,Let we use a vector to represent the image line L of l. Since We have, or It is the equation of projecting plane, the normal is . Thus, we will use the normal of the projecting plane of 3D line to denote image plane by,4. Digital Image,Sampling: digitalize in image plane ( directions) say, , ,and so on. quantization: digitalize in image intensi