Course Details

Subject {L-T-P / C} : EE6148 : Computer Vision {3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. Dipti Patra

Syllabus

REPRESENTATION: Chain codes, Polygonal approximations, Signatures, Boundary segments, Skeletons, DESCRIPTION: Boundary descriptors, Shape numbers, Fourier descriptors, Statistical moments, Regional descriptors, Topological descriptors, Texture, Moment invariants, Use of principal components for description, Relational descriptors. OBJECT RECOGNITION: Patterns and pattern classes, Recognition based on decision-theoretic methods, Matching, Optimum statistical classifiers, Neural networks, Structural Methods, Matching Shape Numbers, String Matching, IMAGE UNDERSTANDING: Active contour models, Point distribution models, Scene labeling and constraint propagation, Depth perception problems, 3-D Vision, Stereo Geometry and correspondence, Motion analysis, Multiresolution Image Processing, Applications of Computer Vision: Remote Sensing, Biomedical Imaging, Document Processing, Target tracking.

Course Objectives

  1. To understand the geometric relationships between 2D images and the 3D world.
  2. To understand and implement the common methods for robust image matching and alignment.
  3. To have exposure to object and scene recognition and categorization from images.
  4. To develop the practical skills necessary to build computer vision applications.

Course Outcomes

• Be familiar with both the theoretical and practical aspects of computer vision.
• Have implemented common methods for robust image matching and alignment.
• Understand the geometric relationships between 2D images and the 3D world.
• Have gained exposure to object and scene recognition and categorization from images.
• Developed the practical skills necessary to build computer vision applications.

Essential Reading

  1. Milan Sonka, Vaclav Hlavac, Roger Boyle, Image Processing, Analysis, and Machine Vision, Cengage Learning, 2008
  2. Richard Szeliski, Computer Vision: Algorithms and Applications, Springer, 2010

Supplementary Reading

  1. L.G. Shapiro, G. C. Stockman, Computer Vision, Prentice Hall
  2. T. Morris, Computer Vision and Image Processing, Palgrave McMillan

Journal and Conferences

  1. IEEE Transaction on Pattern Analysis and Machine Intelligence
  2. IEEE conference on Computer Vision & Pattern Recognition