Outline

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The objective of this course is to introduce the essential concepts of computer vision and an in depth methods of recent computer vision algorithms. Course contains multiple assignments and a project. Each student is required to present one paper from the subtopics (Segmentation, Detection and Tracking). We will be programming in Python to create computer vision algorithms and homework assignments.

Class

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TTh 10:00 am - 11:30 am, Location: S 202

Information

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Instructor: Shishir Shah | Office: PGH 215 | Office Hours: T 11:30 AM-1:00 PM or by appointment.

TA Information

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TA: Zhenggang Li | Office: TBA | Office Hours: TBA

Tentative Topics

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Computer vision basics, Image segmentation, Object detection and Tracking

Tentative Grading:

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Assignments: 60%, Project: 30%, Paper presentation: 10%

Recommended Text

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Computer Vision: A Modern Approach by D. A. Forsyth and J. Ponce, Prentice Hall, Upper Saddle River, N.J., 2003.

Supplement

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Assigned Readings

Notes

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Attendance and participation in class in encouraged. Programming assignments will test your understanding of the subject matter covered in class and assigned readings. Assignments will require programming in Python. All students are expected to complete a project and provide a written report on the last day of class. Project presentations will be held in class in the last week before exams. All assignments submitted after the due date will accrue a penalty of 33% per day.

Updates

Welcome to the Spring 2020 offering of Computer Vision (COSC 6373) course

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