A Review on Video-Based Human Activity Recognition

DOI Web Site 4 Citations
  • Shian-Ru Ke
    Department of Electrical Engineering, University of Washington, Seattle, WA 98195-2500, USA
  • Hoang Thuc
    Department of ETE, Danang University of Technology, Danang, Vietnam
  • Yong-Jin Lee
    Department of Electrical Engineering, University of Washington, Seattle, WA 98195-2500, USA
  • Jenq-Neng Hwang
    Department of Electrical Engineering, University of Washington, Seattle, WA 98195-2500, USA
  • Jang-Hee Yoo
    Video Surveillance Research Section, ETRI, 305-700 Daejeon , Korea
  • Kyoung-Ho Choi
    Department of Information & Electronics Engineering, Mokpo National University, Jeollanam-do 534-729, Korea

Description

<jats:p>This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems.</jats:p>

Journal

  • Computers

    Computers 2 (2), 88-131, 2013-06-05

    MDPI AG

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