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Spring 2014 Semester
Apr 24, 2014
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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; restricted to students in the College of Computer and Information Science.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Computer Science Department

Course Attributes:
GSCS Computer & Info Science

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate
Must be enrolled in one of the following Colleges:     
      Coll of Computer & Info Sci
Must be enrolled in one of the following Classifications:     
      Graduate

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

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