Abstract
This paper presents two variations of a Hough-voting framework used for action recognition and shows classification results for low-resolution video and videos depicting human interactions. For low-resolution videos, where people performing actions are around 30 pixels, we adopt low-level features such as gradients and optical flow. For group actions with human-human interactions, we take the probabilistic action labels from the Hough-voting framework for single individuals and combine them into group actions using decision profiles and classifier combination.
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Waltisberg, D., Yao, A., Gall, J., Van Gool, L. (2010). Variations of a Hough-Voting Action Recognition System. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds) Recognizing Patterns in Signals, Speech, Images and Videos. ICPR 2010. Lecture Notes in Computer Science, vol 6388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17711-8_31
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DOI: https://doi.org/10.1007/978-3-642-17711-8_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17710-1
Online ISBN: 978-3-642-17711-8
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