Drift in correlation algorithms for high speed video trackers

David C. Dayton; Rudolph Nolasco

doi:10.1117/12.2274985

6 September 2017 Drift in correlation algorithms for high speed video trackers

David C. Dayton, Rudolph Nolasco

Proceedings Volume 10410, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017; 104100D (2017) https://doi.org/10.1117/12.2274985
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

The FITTS correlation algorithm has been widely used for over forty years in high speed video trackers. It has the advantage that it is very simple implement in a digital processor with a small number of calculations. At each step the algorithm attempts to estimate the shift between an image of a moving target and a proto-type image. There are several well-known short comings of the FITTS algorithm. First the error in the shift estimate increases if the shift is greater than one pixel of the digital image. Secondly all correlation based tracking algorithms are susceptible to low frequency drift. These errors can force a lower tracker closed loop bandwidth to maintain track loop stability. In this paper we examine in an intuitive manner the underlying cause of the drift and approaches to its mitigation.

Conference Presentation

Citation Download Citation

David C. Dayton and Rudolph Nolasco "Drift in correlation algorithms for high speed video trackers", Proc. SPIE 10410, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017, 104100D (6 September 2017); https://doi.org/10.1117/12.2274985

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