Course Details
Subject {L-T-P / C} : EC6603 : Computer Vision { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. Sukadev Meher
Syllabus
MODULE-I: Image formation and image models: cameras, geometric camera models, geometric camera calibration, radiometry measuring light, sources, and shading, color [5 Hours]
MODULE-II: Early Vision - Single Image: linear filters, edge detection, texture [6 Hours]
MODULE-III: Early Vision - Multiple Images: the geometry of multiple views, stereopsis [5 Hours]
MODULE-IV: Mid-Level Vision: Segmentation by clustering, segmentation by fitting a model [7 Hours]
MODULE-V: High-Level Vision: Learning to classify- classification, error and loss, Major classification strategy, Practical methods for building classifiers, Classifying Images- Building good image features, Classifying images of single objects [8 Hours]
MODULE-VI: Applications like object recognition, character recognition, face recognition, gait recognition [5 Hours]
Course Objectives
- To understand how an image is formed
- To understand image filtering techniques
- To get familiarized with image segmentation techniques
- To understand how a classifier works
Course Outcomes
After completion of this course, a student will be able: <br />1) To understand the fundamental concepts of image acquisition and image processing systems <br />2) To analyze image processing and computer vision systems and algorithms <br />3) To design and develop image processing and computer vision systems and algorithms <br />4) To design various object recognition systems <br />5) To carry out research and development in the field of computer vision systems and algorithms.
Essential Reading
- David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach, Pearson Education , 2008
- R C Gonzalez and R E Woods, Digital Image Processing, Pearson , 2014
Supplementary Reading
- Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press , 2004
- Richard Szeliski, Computer Vision: Algorithms and Applications, Springer , 2011