In this course you will learn to develop and analyze the algorithms and mathematics for computer vision problems and applications. You will learn to implement vision algorithms efficiently for use in research or industry.
Upon completion of this course, students should be able to:
Recognize and describe both the theoretical and practical aspects of computing with images. Connect issues from Computer Vision to Human Vision Describe the foundation of image formation and image analysis. Understand the basics of 2D and 3D Computer Vision. Become familiar with the major technical approaches involved in computer vision. Describe various methods used for registration, alignment, and matching in images. Get an exposure to advanced concepts, including state of the art deep learning architectures, in all aspects of computer vision. Build computer vision applications with python and the pytorch framework.
- proj 1: Images as Functions
- Proj 2: Detecting Lines and Circles using Hough Transform .
- Proj 3: Local Feature Matching .
- Proj 4: Camera Parameter Estimation .