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# 计算机视觉-华中科技大学研究生院_图文

§10.2 超分辨率与去模糊 §10.3 图像合成 §10.4 纹理分析与合成 第十一章 立体匹配 §11.1 对极几何 §11.2 稀疏和稠密匹配 §11.3 局部和全局方法 §11.4 多视立体视觉 第十二章 三维重建 §12.1 形状恢复 §12.2 三位表示 §12.3 基于模型的重建 §12.4 基于图像和视频的绘制

Aim and Scope： The goal of computer vision is to compute properties of the three-dimensional world from digital images. Problems in this field include identifying the 3D shape of an environment, determining how things are moving, and recognizing familiar people and objects, all through analysis of images and video. This course provides an introduction to computer vision, including such topics as feature detection, image segmentation, motion estimation, 3D shape reconstruction, and object recognition. Course Outline: Chapter 1 Introduction §1.1 What is computer vision? §1.2 A brief history §1.3 Course overview Chapter 2 Image formation §2.1 Geometric primitives and transformations §2.2 Photometric image formation Chapter 3 Image pre-processing §3.1 Point operators and filtering §3.2 Pyramids and wavelets Chapter 4 Feature detection and matching §4.1 Points and patches §4.2 Edges §4.3 Lines Chapter 5 Segmentation §5.1 Boundary-based methods §5.2 Region-based methods §5.3 Graph-based methods Chapter 6 Feature-based alignment §6.1 2D and 3D feature-based alignment §6.2 Pose estimation §6.3 Geometric intrinsic calibration Chapter 7 Dense motion estimation §7.1 Motion models §7.2 Translational alignment §7.3 Global alignment Chapter 8 Structure from motion §8.1 Two-frame structure from motion §8.2 Bundle adjustment §8.3 Constrained structure and motion Chapter 9 Recognition §9.1 Object detection

§9.2 Instance and category recognition §9.3 Context and scene understanding Chapter 10 Computational photography §10.1 Photometric calibration §10.2 Super-resolution and blur removal §10.3 Image matting and compositing §10.4 Texture analysis and synthesis Chapter 11 Stereo correspondence §11.1 Epipolar geometry §11.2 Sparse and dense correspondence §11.3 Local and global methods §11.4 Multi-view stereo Chapter 12 3D reconstruction §12.1 Shape from X §12.2 3D representations §12.3 Model-based reconstruction §12.4 Image and video based rendering Textbook： Richard Szeliski, Computer Vision: Algorithms and Applications Reference： 1. D. A. Forsyth, J. Ponce, Computer Vision: A Modern Approach 2. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision 3．R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification 本课程达到国际一流水平研究生课程水平的标志： 1.师资方面： 任课教师均有国际一流大学留学经验。 2.教学内容方面： 教学内容与国际一流大学教学内容相符。 3.教学方式方面： 考核方式采取与国际一流大学相同的笔试加项目（项目又分为口头和书面报 告）的形式。 4.教材方面： 采用目前国际一流大学最通用的教材和参考书。 5.其它：