CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved harmony search from ensemble of music players
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Recent Advances in Harmony Search Algorithm
Recent Advances in Harmony Search Algorithm
An Intelligent Tuned Harmony Search algorithm for optimisation
Information Sciences: an International Journal
Computers & Mathematics with Applications
Information Sciences: an International Journal
Survey A survey on applications of the harmony search algorithm
Engineering Applications of Artificial Intelligence
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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.