IT813
Course Name:
Computer Vision (IT813)
Programme:
M.Tech (IT)
Category:
Elective Courses (Ele)
Credits (L-T-P):
(3-0-0) 3
Content:
Introduction to Computer Vision, Color + Math basics, Linear Algebra, Pixels and filters, Edge detection, Features and fitting, Feature descriptors, Resizing, Semantic segmentation, Clustering, Object recognition, Dimensionality reduction, Face identification, Visual Bag of Words, Detecting objects by parts, Image classification, Motion Tracking, Introduction to Deep Learning.
References:
Sonka M., Hlavac V., Boyle R., “Image Processing Analysis and Machine Design”. PWS Publishers
Ballard D., brown C., “Computer Vision”, Prentice Hall
R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison Wesley, 1992.
Digital Image Processing and Computer Vision”;; John Wiley and Sons, 1989.
Robert J. Schallkoff , Pattern Recognition: Statistical. Structural & Neural Approaches, John Wiley and Sons, 1992.
D. A. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Pearson Education, 2003.
Richard Szeliski, Computer Vision: Algorithms and Applications, Springer-Verlag, 2011.
Department:
Information Technology