Course 2018
| Instructors: | Marc Pollefeys, Luc Van Gool, Vittorio Ferrari |
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| Teaching assistants: |
CVG part:
Peidong Liu,
Nikolay Savinov,
Pablo Speciale,
Katarina Tóthová,
Viktor Larsson,
CVL part:
Yawei Li,
Vaishakh Patil,
Andrii Ihnatov,
Stamatios Georgoulis,
Bhaskara Rao Chintada
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| Lectures: | Wednesdays from 13:15-16:00 in CHN C 14 |
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| Exercises: | Thursdays from 15:15-16:00 in CHN C 14 |
Catalog: |
263-5902-00L Computer Vision |
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No exercise session on 20.09.2018
No exercise session on 25.10.2018
No exercise session on 20.12.2018
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Computer Vision (following Tomaso Poggio, MIT): Computer Vision, formerly an almost esoteric corner of research and regarded as a field of research still in its infancy, has emerged to a key discipline in computer science. Vision companies have emerged and commercial applications become available, ranging from industrial inspection and measurements to security database search, surveillance, multimedia and computer interfaces. Computer Vision is still far from being a solved problem, and most exciting developments, discoveries and applications still lie ahead of us. Understanding the principles of vision has implications far beyond engineering, since visual perception is one of the key modules of human intelligence.
Important: course is managed through moodle
All the lectures and exercises will be posted on moodle.
You also have to submit the exercises there. If you have questions, there is a forum on moodle.
You can also ask private questions to TAs through the moodle system. Please, don't email questions unless it's very urgent.
Course Objectives
The objectives of this course are:
| 1. | To introduce the fundamental problems of computer vision. |
| 2. | To introduce the main concepts and techniques used to solve those. |
| 3. | To enable participants to implement solutions for reasonably complex problems. |
| 4. | To enable participants to make sense of the computer vision literature. |
Course Topics
Camera models and calibration, invariant features, Multiple-view geometry, Model fitting, Stereo Matching, Segmentation, 2D Shape matching, Shape from Silhouettes, Optical flow, Structure from motion, Tracking, Object recognition, Object category recognition
Target Audience
The target audience of this course are Master students, that are interested to get a basic understanding of computer vision.
Requirements
Fundamentals of calculus and linear algebra, basic concepts of algorithms and data structures, basic programming skills in Matlab and C.
Some useful links
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