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Course Detail

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


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.


  • 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.

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