A fast kernel tracking algorithm based on local gradient histograms

Daniel Miramontes-Jaramillo; Vitaly Kober

doi:10.1117/12.2022766

26 September 2013 A fast kernel tracking algorithm based on local gradient histograms

Daniel Miramontes-Jaramillo, Vitaly Kober

Proceedings Volume 8856, Applications of Digital Image Processing XXXVI; 885618 (2013) https://doi.org/10.1117/12.2022766
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

Abstract

A common tracking algorithm solves several problems such as detection and localization of an object of interest in the scene, invariance to different movement directions of the object, occlusion of the target, when the target exits or reenters to the scene and so on. Nowadays the frame rates are various from 30 FPS (frames per second) to 300 FPS in special devices. Tracking algorithms can be classified as follows: point trackers, kernel trackers, and silhouette trackers. In this work, we propose a kernel tracking algorithm based on a local gradient histogram matching algorithm and prediction of the target position in video sequence frames.

Citation Download Citation

Daniel Miramontes-Jaramillo and Vitaly Kober "A fast kernel tracking algorithm based on local gradient histograms", Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 885618 (26 September 2013); https://doi.org/10.1117/12.2022766

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