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Percentage of human-occupied areas for fall detection from two views

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Abstract

Falls are the major causes of fatal injury for the elderly population. To remedy this, several elderly people monitoring systems with fall detection functionality have been proposed. In this work, we investigate a video-based method of detecting fall incidents from multiple cameras. Our goal is to propose a novel method to detect falls on the floor with a multiple-camera system using the percentage of human-occupied areas. We suggest the use of two relatively orthogonal views to estimate the percentage of the surface of the person which is in contact with the ground according to the foreground information of each camera. These features are computed to differentiate by an automatic manner the lying on floor posture which can be considered as fall to other position such as standing up or sitting. This method is evaluated on a public multi-view fall detection dataset which contains videos of a healthy subject who performed 24 realistic scenarios. These scenarios show 22 fall events and 24 confounding events. The results of our experiments show that our proposed algorithm achieved 95.8 % sensitivity and 100 % specificity with less computational costs than state-of-the-art methods.

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Acknowledgments

This work is partially financially supported by the Association AS2V and Fondation Jacques De Rette, France. Mikaël A. Mousse is grateful to the “Service de Coopération et d’Action Culturelle de l’Ambassade de France au Bénin”. The authors also appreciate the comments provided by the reviewers as these have improved the manuscript.

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Authors and Affiliations

  1. EA 4491, LISIC, Laboratoire d’Informatique Signal et Image de la Côte d’Opale, Université Littoral Côte d’Opale, 62228, Calais, France

    Mikaël A. Mousse & Cina Motamed

  2. Unité de Recherche en Informatique et Sciences Appliquées, Institut de Mathématiques et de Sciences Physiques, Porto-Novo, Benin

    Mikaël A. Mousse & Eugène C. Ezin

Authors
  1. Mikaël A. Mousse
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  2. Cina Motamed
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  3. Eugène C. Ezin
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Correspondence to Mikaël A. Mousse.

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Mousse, M.A., Motamed, C. & Ezin, E.C. Percentage of human-occupied areas for fall detection from two views. Vis Comput 33, 1529–1540 (2017). https://doi.org/10.1007/s00371-016-1296-y

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  • DOI: https://doi.org/10.1007/s00371-016-1296-y

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