Basic topics of computer vision, and image processing -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. Recent Advances in Computer vision.

Programming:

Python will be the main programming environment for the assignments. The following book (Python programming samples for computer vision tasks) is freely available. Python for Computer Vision. For mini- projects, a Processing programming language can be used too (strongly encouraged for android application development)

Same as Reference

1. Computer Vision: Models, Learning, and Interface, Simon Prince, Cambridge University Press.

2. Fundamentals of Computer Vision, Mubarak Shah, University of Central Florida, 1997.

3. Computer Vision: Algorithms and Applications Richard Szeliski, Springer, 2010.

4. Computer Vision: A Modern Approach, Forsyth and Ponce, Prentice-Hall, 2002.

5. Vision Science, Palmer, MITPress,1999.

6. Pattern Classification, Duda, Hart and Stork, 2nd Edition, Wiley, 2000.

7. Probabilistic Graphical Models: Principles and techniques, Koller and Fried man, MIT Press, 2009.

8. Linear Algebra and Its Applications, Strang, Gilbert. 2/e, Academic Press, 1980.