A swarm-intelligence based algorithm for face tracking
by Yuhua Zheng, Yan Meng
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 7, No. 3, 2009

Abstract: This article presents a new face tracking algorithm that employs a swarm-intelligence based method particle swarm optimisation (PSO). Firstly, all potential solutions are projected into a high-dimensional space where particles are initialised. Then, particles are driven by PSO rules to search for the solutions. The face is tracked when the particles reach convergence. Furthermore, a multi-feature model is also proposed for face description to enhance the tracking accuracy and efficiency. The proposed model and algorithm are object-independent and can be used for any free-selected object tracking. Experimental results on face tracking demonstrate that the proposed algorithm is efficient and robust in visual object tracking under dynamic environments with real-time performance.

Online publication date: Wed, 15-Jul-2009

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