General relationship for optimal tracking performance

Markus Vincze; Carl F. R. Weiman

doi:10.1117/12.256298

29 October 1996 General relationship for optimal tracking performance

Markus Vincze, Carl F. R. Weiman

Proceedings Volume 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling; (1996) https://doi.org/10.1117/12.256298
Event: Photonics East '96, 1996, Boston, MA, United States

Abstract

Visual tracking is a vital task in active vision research, traffic surveillance, face following, robotics, and many other applications. This paper investigates the principles of finding optimal tracking performance depending on image tesselation and window size. Square windows reach best performance when image sampling time equals image processing time. This is valid in all cases where the algorithm investigates each pixel in the window and for both tracking with fixed or steered camera/s. Linear windows can improve tracking performance, though performance is limited, too. Best performance yield space-variant image tessellations. Image pyramids or log-polar sampled images show steadily increasing tracking performance with increasing sensor size. The reason is that the resolution drops as sensor size increases.

Citation Download Citation

Markus Vincze and Carl F. R. Weiman "General relationship for optimal tracking performance", Proc. SPIE 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling, (29 October 1996); https://doi.org/10.1117/12.256298

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