A fast kernel tracking algorithm based on local gradient histograms

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.