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Automated Fall Detection Using Computer Vision

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Intelligent Human Computer Interaction (IHCI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11278))

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Abstract

The population of elderly people is increasing day-by-day in the world. One of the major health issues of an old person is injury during a fall and this issue becomes compounded for elderly people living alone. In this paper, we propose a novel framework for automated fall detection of a person from videos. Background subtraction is used to detect the moving person in the video. Different features are extracted by applying rectangle and ellipse on human shape to detect the fall of a person. Experiments have been carried out on the UR Fall Dataset which is publicly available. The proposed method is compared with existing methods and significantly better results are achieved.

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Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Pramod Kumar Soni & Ayesha Choudhary

Authors
  1. Pramod Kumar Soni
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  2. Ayesha Choudhary
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Corresponding author

Correspondence to Ayesha Choudhary .

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Editors and Affiliations

  1. Indian Institute of Information Technology, Allahabad, India

    Uma Shanker Tiwary

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Soni, P.K., Choudhary, A. (2018). Automated Fall Detection Using Computer Vision. In: Tiwary, U. (eds) Intelligent Human Computer Interaction. IHCI 2018. Lecture Notes in Computer Science(), vol 11278. Springer, Cham. https://doi.org/10.1007/978-3-030-04021-5_20

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  • DOI: https://doi.org/10.1007/978-3-030-04021-5_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04020-8

  • Online ISBN: 978-3-030-04021-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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