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ECE 5554: Computer
Vision Systems
[Fall, 2005]; Dr. Pushkin Kachroo; CRN: 95427;
Credits: 3
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Analysis of digital images and
three-dimensional scenes. Image acquisition, representation of two- and
three-dimensional shapes, visual cues for range estimation. Image filtering and
histogram-based analysis for image enhancement, noise suppression, edge
detection, region detection, and image segmentation. Introduction to such
topics as visual texture, stereo vision, structured-light ranging, and motion
analysis. |
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Taught by |
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231-2976 |
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Listserve |
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Grading |
HW/Projects: 30%; Tests/Final: 65%; Attendance: 5% Guaranteed Grades: A- ( > 90%); B- ( > 80%); C- ( > 70%); |
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Lecture Room |
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Lecture Time |
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Office Hours |
Location:
345 |
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Textbook |
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T.A. |
T.A.;
Email:ta@vt.edu |
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Software |
Any C/C++ compiler (Visual C++
preferred) |
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Schedule |
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Dates |
Days |
Topics |
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Aug 22 |
T |
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Aug29 |
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Sep05 |
T |
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Sep12 |
T |
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Sep19 |
T |
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Sep26 |
T |
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Oct03 |
T |
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Oct10 |
T |
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Oct17 |
T |
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Oct24 |
T |
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Oct31 |
T |
No class |
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Nov07 |
T |
linelabel, color |
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Nov14 |
T |
Shape/shading |
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Nov21 |
T |
Thanksgiving
Break |
No Class |
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Nov28 |
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Test |
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Dec05 |
T |
Class Presentations |
Final Reports
Due |
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15th |
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Final Exam |
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Major Measurable Learning Objectives:
Having successfully completed
this course, the student will be able to:
(1) select imaging devices and
illumination sources for a given application;
(2) design and implement
algorithms that perform edge detection, noise suppression,
image thresholding, histogram
analysis, region detection, and region labeling;
(3) compute edge and region
properties that can be used for higher-level analysis;
(4) analyze problems that
involve perspective projection or orthographic projection;
(5) assess the performance of
vision-based range- and shape-estimation systems.