Computer Vision (CS 518)

2022 Fall
Faculty of Engineering and Natural Sciences
Computer Sci.& Eng.(CS)
3
10
Erchan Aptoula erchan.aptoula@sabanciuniv.edu,
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English
Doctoral, Master
--
Formal lecture
Interactive,Communicative,Task based learning,Case Study
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CONTENT

This course covers the basic concepts in machine vision, including sensing and perception, 2D image analysis, pattern classification, physics-based vision, stereo and motion, and solid model recognition, image formation and representation, multi-scale analysis, segmentation, contour and region region analysis, reconstruction of depth based on stereo, text shading and motion, and analysis and recognition of objects and scenes using statistical and model-based techniques.

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 20
Midterm 15
Participation 5
Presentation 15
Homework 45

RECOMENDED or REQUIRED READINGS

Textbook

Richard Szeliski, Computer Vision: Algorithms and Applications
David Forsyth and Jean Ponce, Computer Vision: A Modern Approach (Second Edition)
Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision (Second Edition)
Rafael Gonzalez and Richard Woods, Digital Image Processing