Back close

Course Detail

Course Name Computer Vision
Course Code 15CSE340
Program B. Tech. in Computer Science and Engineering
Year Taught 2019

Syllabus

Unit 1

Introduction, Image Formation – geometric primitives and transformations, photometric image formation, digital camera, Image Processing – point operators, linear filtering, neighbourhood operators, fourier transforms, segmentation.

Unit 2

Feature Detection and Matching – points and patches, edges, lines, Feature-based Alignment – 2D, 3D feature-based alignment, pose estimation, Image Stitching, Dense motion estimation – Optical flow – layered motion, parametric motion, Structure from Motion.

Unit 3

Recognition – object detection, face recognition, instance recognition, category recognition, Stereo Correspondence – Epipolar geometry, correspondence, 3D reconstruction.

Text Books

  • Szeliski R., “Computer Vision: Algorithms and Applications”, Springer, 2010.

Resources

  • Shapiro L. G. and Stockman G., “Computer Vision”, Prentice Hall, 2001.
  • Forsyth D. A. and Ponce J., “Computer Vision – A Modern Approach”, Second Edition, Pearson Education, 2012.
  • Davies E. R., “Machine Vision: Theory, Algorithms, Practicalities”, Morgan Kaufmann, 2004.
  • Jain R., Kasturi R. and Shunck B. G., “Machine Vision”, McGraw Hill, 1995.

DISCLAIMER: The appearance of external links on this web site does not constitute endorsement by the School of Biotechnology/Amrita Vishwa Vidyapeetham or the information, products or services contained therein. For other than authorized activities, the Amrita Vishwa Vidyapeetham does not exercise any editorial control over the information you may find at these locations. These links are provided consistent with the stated purpose of this web site.

Admissions Apply Now