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Vision Based Human Activity Recognition: A Review

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Advances in Computational Intelligence Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 513))

Abstract

Human activity recognition (HAR) is an important research area in computer vision due to its vast range of applications. Specifically, the past decade has witnessed enormous growth in its applications, such as Human Computer Interaction, intelligent video surveillance, ambient assisted living, entertainment, human-robot interaction, and intelligent transportation systems. This review paper provides a comprehensive state-of-the-art survey of different phases of HAR. Techniques related to segmentation of the image into physical objects, feature extraction, and activity classification are thoroughly reviewed and compared. Finally, the paper is concluded with research challenges and future directions.

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Authors and Affiliations

  1. School of Computing and Communications Infolab21, Lancaster University, Lancester, LA1 4WA, UK

    Allah Bux & Plamen Angelov

  2. Department of Computer Science, COMSATS Institute of Information Technology, Lahore, Pakistan

    Allah Bux & Zulfiqar Habib

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  1. Allah Bux
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  2. Plamen Angelov
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  3. Zulfiqar Habib
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Editors and Affiliations

  1. School of Computing and Communications, Lancaster University Bailrigg School of Computing and Communications, Lancaster, United Kingdom

    Plamen Angelov

  2. School of Computing, University of Portsmouth School of Computing, Portsmouth, Hampshire, United Kingdom

    Alexander Gegov

  3. School of Comp. Sci. & Digital Media, Robert Gordon University School of Comp. Sci. & Digital Media, Aberdeen, United Kingdom

    Chrisina Jayne

  4. Ins. of Mathematics, Physics & Comp. Sci, Aberystwyth University Ins. of Mathematics, Physics & Comp. Sci, Aberystwyth, United Kingdom

    Qiang Shen

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Bux, A., Angelov, P., Habib, Z. (2017). Vision Based Human Activity Recognition: A Review. In: Angelov, P., Gegov, A., Jayne, C., Shen, Q. (eds) Advances in Computational Intelligence Systems. Advances in Intelligent Systems and Computing, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-319-46562-3_23

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