Introduction
This is an advanced course on graduate computer vision and computational photography. This course will explore image formation, image features, image segmentation, image stitching, image recognition, motion estimation, 3D point clouds and will touch upon basics of augmented reality.
For further information, please see the course syllabus.
General Information
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| Class Time |
Tuesdays & Thursdays 12:30PM - 1:45PM |
| Location | CSI 2118 |
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| Teaching Assistants |
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If you cannot make it to any of the above office hours due to some commitment, please do e-mail us and fix up an appointment so that we can help you.
Piazza
Important class announcements will be made through the Piazza system. The class piazza can be found here.
Acknowledgements
Special thanks to Dr. Cornelia Fermüller for providing most of the lecture materials for this class.
A lot of projects in this course are based on graduate and doctoral courses from other universities. Links to these courses can be found in the Logistics section under the title
Other Good Computer Vision Courses and Tutorials.
The course website is based on Prof. David Mount's website for CMSC 754: Computational Geometry found here. We loved the simplicity and lightness of his website design.
Server Login
The server login procedure can be found here.
Some Useful Resources
The links to e-books of the reference books if available are given in the Logistics section under the title Reference Books.
Online resource of computer vision topics (contains short descriptions and tutorials on basic and advanced topics)
Image Processing Learning resources
Image Processing Online Journal. Contains many good algorithms with implementations for free.
MATLAB Speed Up Tricks
Image Filtering Tutorial
Peter Kovesi's awesome computer vision and image processing functions for MATLAB. Literally has everything you need.
VLFeat for MATLAB. Has a lot of new algorithms and supports all platforms.
Peter Corke's Machine Vision Toolbox for MATLAB. Has a lot of new algorithms and supports all platforms.
Some slides for using MATLAB in Image Processing from ETH Zurich
MATLAB tutorial from University of Toronto
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