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Computer Science

Courses

Introduction to Computer Vision
Text code : CSE527 / Credit : 3
  • Prerequisites Limited to CSE graduate students; others, permission of instructor
  • Textbook information Multiple view geometry in computer vision by Hartley, R., & Zisserman, A., Cambridge university press, 2003. Computer vision: algorithms and applications by Szeliski, R., & Zisserman, A., Springer Nature, 2022.

Course Coordinator Francois Rameau
Description

 Introduction to basic concepts in computer vision. Low-level image analysis, image formation, edge detection, segmentation. Image transformations for image synthesis methods for 3D scene reconstruction, motion analysis, object recognition.

Prerequisite  
Credits 3 Credits
Course Outcomes
  • Understand the theoretical foundations of projective geometry and image formation.
  • Apply traditional and deep learning methods for various problems such as keypoint detection, segmentation, and object detection.
  • Reconstruct 3D scenes using multiview geometry and deep-learning-based approaches like NeRF.
  • Develop practical skills in computer vision engineering through a hands-on project.
Textbook Multiple view geometry in computer vision by Hartley, R., & Zisserman, A., Cambridge university press, 2003.
Computer vision: algorithms and applications by Szeliski, R., & Zisserman, A., Springer Nature, 2022.
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