Lectures: Thursdays 13:30-15:30, Ullman 707

Tutorials: Thursdays 15:30-16:30, Ullman 707

Overview:

This is an introductory level course in Computer Vision, which describes basics and common techniques and algorithms and some recent deep-learning based methods. The Homework include hands-on experience with some problems and algorithms.

Prerequisites:

A passing grade in an Image Processing course is required. Recommended such courses are "Signal and Image Processing by Computer" (236327) or "Image Processing and Analysis" (046200). Students without the prerequisite must first receive the lecturer's agreement to participate in the course, and participate in a basic image processing crash course (including one additional HW assignment) in the beginning of the semester.

Grading Policy: Four equally weighted homework assignments (50%). Final exam (50%).