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Motion Boundary Trajectory for Human Action Recognition

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Computer Vision - ACCV 2014 Workshops (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9008))

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Abstract

In this paper, we propose a novel approach to extract local descriptors of a video, based on two ideas, one using motion boundary between objects, and, second, the resulting motion boundary trajectories extracted from videos, together with other local descriptors in the neighbourhood of the extracted motion boundary trajectories, histogram of oriented gradients, histogram of optical flow, motion boundary histogram, can be used as local descriptors for video representations. The motion boundary approach captures more information between moving objects which might be caused by camera movements. We compare the performance of the proposed motion boundary trajectory approach with other state-of-the-art approaches, e.g., trajectory based approach, on a number of human action benchmark datasets (YouTube, UCF sports, Olympic Sports, HMDB51, Hollywood2 and UCF50), and found that the proposed approach gives improved recognition results.

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Acknowledgment

This work was financially supported by Fundo para o Desenvolvimento das Ciencia das e da Tecnologia, Macau SAR Grant Number 034/2011/A2. The authors would like to thank Associate Prof. Markus Hagenbuchner, University of Wollongong and Prof. Franco Scarselli, University of Siena, for many helpful comments on the proposed approach.

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Authors and Affiliations

  1. Faculty of Information Technology, Macau University of Science and Technology, Macau, China

    Sio-Long Lo & Ah-Chung Tsoi

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  1. Sio-Long Lo
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  2. Ah-Chung Tsoi
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Correspondence to Sio-Long Lo .

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Editors and Affiliations

  1. Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India

    C.V. Jawahar

  2. Institue of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

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Lo, SL., Tsoi, AC. (2015). Motion Boundary Trajectory for Human Action Recognition. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9008. Springer, Cham. https://doi.org/10.1007/978-3-319-16628-5_7

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  • DOI: https://doi.org/10.1007/978-3-319-16628-5_7

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  • Online ISBN: 978-3-319-16628-5

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