Computer Vision for Student Competitions: Object Tracking

Version 1.0.0.0 (7.7 MB) by MathWorks Student Competitions Team
Object Tracking (Chapter 8) : Computer Vision for Student Competition Teams
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Updated 23 Mar 2017
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Learn how to track an object across video frames. Object tracking using histogram based tracking, tracking occluded or hidden objects using a Kalman Filter, and multiple objects tracking are covered. An example of tracking a moving ball will be used.

Cite As

MathWorks Student Competitions Team (2024). Computer Vision for Student Competitions: Object Tracking (https://github.com/sseshadr/auvsi-cv-objectTracking), GitHub. Retrieved .

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1.0.0.0

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Published to GitHub.
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