Abstract
We propose a robust and efficient method for accurate detecting and localizing complex human action in video in space and time dimensions using spatio-temporal templates. A simple but effective motion descriptor based on the motion-compensated frame difference is designed for template representation, which is resistant to the deformation of posture and cluttered and moving background. A multi-step filtering scheme is adopted to speed up the target candidates localization and matching to the templates. For the template sequence to video registration, we present an extended continuous dynamic programming technique which can compute the matching scores for multiple trajectories simultaneously. Extensive experimental results on different videos have demonstrated the effectiveness of the proposed method.
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Li, H., Sun, F., Guan, Y. (2013). Robust Detection and Localization of Human Action in Video. In: Li, S., et al. Advances in Multimedia Modeling. Lecture Notes in Computer Science, vol 7733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35728-2_25
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DOI: https://doi.org/10.1007/978-3-642-35728-2_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35727-5
Online ISBN: 978-3-642-35728-2
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