Harmony filter: A robust visual tracking system using the improved harmony search algorithm

In this article a novel approach to visual tracking called the harmony filter is presented. It is based on the Harmony Search algorithm, a derivative free meta-heuristic optimisation algorithm inspired by the way musicians improvise new harmonies. The harmony filter models the target as a colour histogram and searches for the best estimated target location using the Bhattacharyya coefficient as a fitness metric. Experimental results show that the harmony filter can robustly track an arbitrary target in challenging conditions. We compare the speed and accuracy of the harmony filter with other popular tracking algorithms including the particle filter and the unscented Kalman filter. Experimental results show the harmony filter to be faster and more accurate than both the particle filter and the unscented Kalman filter.

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