Course Details
Subject {L-T-P / C} : CS4374 : Computer Vision Laboratory { 0-0-3 / 2}
Subject Nature : Practical
Coordinator : Prof. Sambit Bakshi
Syllabus
A. Course Introduction, The four Rs of computer vision
B. Cameras and Lenses, Camera calibration, View geometry and homograpy
C. Image Filtering, Hough transformation
D. Image Representations: pyramids
E. Textures and patterns
F. Color understanding by computer, color models and representations
G. Global and Local Features
H. Multiview Geometry
I. Affine Transformations and Reconstructions
J. Projective Geometry
K. Model Based Recognition
L. Segmentation and Clustering, Segmentation and Fitting
M. Shape modelling and rendering
N. Tracking
O. Example based methods in CV: face recognition, medical imaging, UAV navigation
Course Objectives
- understand the typical steps for solution of image processing/vision problems: pre-processing, segmentation, <br />description, and recognition
- possess knowledge and understanding of basic and some advanced methods for each step in the <br />process
- be able to choose appropriate methods and implement solutions to small-scale image processing and <br />vision problems
Course Outcomes
The students will be aware of different application areas in computer vision, and the underlying mechanisms
Essential Reading
- R. Szeliski, Computer Vision: Algorithms and Applications, Springer , ISBN: 9781848829343
- R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press , ISBN: 9780521540513
Supplementary Reading
- R. Gonzalez and R. Woods, Digital Image Processing, Prentice-Hall , ISBN: 013168728X
- R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, Wiley-Interscience Publisher , ISBN: 9780471056690
Journal and Conferences
- Computer Vision and Image Understanding, Elsevier
- International Journal of Computer Vision, Springer