Object tracking with composite optimum filters using non-overlapping signal models

Jose A. Gonzalez-Fraga; Vitaly Kober; Omar Alvarez-Xochihua

doi:10.1117/12.2320909

17 September 2018 Object tracking with composite optimum filters using non-overlapping signal models

Jose A. Gonzalez-Fraga, Vitaly Kober, Omar Alvarez-Xochihua

Proceedings Volume 10752, Applications of Digital Image Processing XLI; 107522J (2018) https://doi.org/10.1117/12.2320909
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

In order to design a tracking algorithm with invariance to pose, occlusion, clutter, and illumination changes of a scene, non-overlapping signal models for input scenes as well as for objects of interest and Synthetic Discriminant Function approach are exploited. A set of optimum correlation filters with respect to peak-to-output energy is derived for different target versions in each frame. A prediction method is utilized to locate a target patch in the coming frame. The algorithm performance is tested in terms of recognition and localization errors in real scenarios and compared with that of the state-of-the-art tracking algorithms.

Citation Download Citation

Jose A. Gonzalez-Fraga, Vitaly Kober, and Omar Alvarez-Xochihua "Object tracking with composite optimum filters using non-overlapping signal models", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522J (17 September 2018); https://doi.org/10.1117/12.2320909

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