Present work introduces a probabilistic recognition scheme for hand gestures. Self organizing feature maps are used to model spatiotemporal information extracted through image processing. Two models are built for each gesture category and, along with appropriate distance metrics, produce a validated classification mechanism that performs consistently during experi-ments on acted gestures video sequences. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Caridakis, G., Pateritsas, C., Drosopoulos, A., Stafylopatis, A., & Kollias, S. (2007). Probabilistic video-based gesture recognition using self-organizing feature maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4669 LNCS, pp. 261–270). Springer Verlag. https://doi.org/10.1007/978-3-540-74695-9_27
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