Abstract
This paper presents an application of the hidden Markov models (HMMs) to the recognition of snakes behaviors, an important and hard problem that, as far as the authors know, has not been tackled before, by the computer vision community. Experiments were conducted using different HMM configurations, including modifications on the number of internal states and the initialization procedures. The best results have shown a 84% correct classification rate, using HMMs with 4 states and an initialization procedure based on the K-Means algorithm. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Gonçalves, W. N., De Andrade Silva, J., Machado, B. B., Pistori, H., & De Souza, A. S. (2007). Hidden Markov models applied to snakes behavior identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4872 LNCS, pp. 777–787). Springer Verlag. https://doi.org/10.1007/978-3-540-77129-6_66
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