Abstract
This paper presents the scatter search particle filter (SSPF) algorithm and its application to real-time hands and face tracking. SSPF combines sequential Monte Carlo (particle filter) and combinatorial optimization (scatter search) methods. Hands and face are characterized using a skin-color model based on explicit RGB region definition. The hybrid SSPF approach enhances the performance of classical particle filter, reducing the required evaluations of the weighting function and increasing the quality of the estimated solution. The system operates on 320×240 live video in real-time. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Pantrigo, J. J., Montemayor, A. S., & Cabido, R. (2005). Scatter search particle filter for 2D real-time hands and face tracking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 953–960). https://doi.org/10.1007/11553595_117
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