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Detailed Course Information


Spring 2013 Semester
Oct 09, 2015
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CS 5330 - Pattern Recognition and Computer Vision
Introduces fundamental techniques for low-level and high-level computer vision. Examines image formation, early processing, boundary detection, image segmentation, texture analysis, shape from shading, photometric stereo, motion analysis via optic flow, object modeling, shape description, and object recognition (classification). Discusses models of human vision (gestalt effects, texture perception, subjective contours, visual illusions, apparent motion, mental rotations, and cyclopean vision). Prereq. Knowledge of linear algebra.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Computer Science Department

Course Attributes:
GSCS Computer & Info Science

Must be enrolled in one of the following Levels:     
Must be enrolled in one of the following Classifications:     

Undergraduate level MATH 2331 Minimum Grade of D- or Graduate Admission REQ

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