smrutil / computer-vision-course-note

Computer Vision Course Note

README

标签： Note

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1. 项目说明

CAP5415-Computer Vision (FALL 2016)课程的学习笔记

2. 课程简要介绍

COURSE GOALS: The course is introductory level computer vision course, suitable for graduate students. It will cover the basic topics of computer vision, and introduce some fundamental approaches for computer vision research:

• Image Filtering, Edge Detection, Interest Point Detectors
• Motion and Optical Flow
• Object Detection and Tracking
• Region/Boundary Segmentation
• Shape Analysis and Statistical Shape Models
• Deep Learning for Computer Vision
• Imaging Geometry, Camera Modeling and Calibration

PRE-REQUEST: Basic Probability/Statistics, a good working knowledge of any programming language (python, matlab, C/C++, or Java), Linear algebra, Vector calculus.

GRADING: Assignments and the term project should include explanatory/clear comments as well as a short report describing the approach, detailed analysis, and discussion/conclusion. 3 Programming assignments 45% (15% each) Term project 35% Mid-Term Exam 20% (tentative date: 15 November 2016, in-class, written)

RECOMMENDED BOOKS (optional)

• Simon Prince, Computer Vision: Models, Learning, and Interface, Cambridge University Press,
• Mubarak Shah, Fundamentals of Computer Vision, Richard Szeliski, Computer Vision: Algorithms and Applications, Springer, 2010 (online draft),
• Forsyth and Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2002,
• Palmer, Vision Science, MIT Press, 1999,
• Duda, Hart and Stork, Pattern Classification (2nd Edition), Wiley, 2000,
• Koller and Friedman, Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009,
• Strang, Gilbert. Linear Algebra and Its Applications 2/e, Academic Press, 1980.

PROGRAMMING Python will be main programming environment for the assignments. Following book (Python programming samples for computer viion tasks) is freely available. Python for Computer Vision For mini-projects, Processing programming language can be used too (strongly encoured for android application development)

3. 学习目标

• 通过课程相关课件及参考书籍了解 computer vision 基础知识
• 选择感兴趣的研究方向
• 将学习体会及收获，编写为 makdown笔记，上传到Github

4. 学习时间

2016.11---2017.3.20

                                                                                from Loser Sun