Abstract
There is biological evidence that human actions are composed out of action primitives, similarly to words and sentences being composed out of phonemes. Given a set of action primitives and an action composed out of these primitives we present a Hidden Markov Model-based approach that allows to recover the action primitives in that action. In our approach, the primitives may have different lengths, no clear “divider” between the primitives is necessary. The primitive detection is done online, no storing of past data is necessary. We verify our approach on a large database. Recognition rates are slightly smaller than the rate when recognizing the singular action primitives.
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Krüger, V. (2006). Recognizing Action Primitives in Complex Actions Using Hidden Markov Models. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_54
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DOI: https://doi.org/10.1007/11919476_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48628-2
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