Human fall detection based on block matching and silhouette area

Mariem Gnouma; Ridha Ejbali; Mourad Zaied

doi:10.1117/12.2268988

17 March 2017 Human fall detection based on block matching and silhouette area

Mariem Gnouma, Ridha Ejbali, Mourad Zaied

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034105 (2017) https://doi.org/10.1117/12.2268988
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

Abstract

Currently, there are several fall detection systems based on video analysis. However, these systems have not yet reached the desired level of appropriateness and robustness. To reduce the risk of falling in insecure environments, a new method is developed in this paper to detect and predict human fall detection. We adopt, in this approach, a Block Matching motion estimation algorithm based on acceleration and changes of the human body silhouette area, which are obtained from a single surveillance camera. It presents an algorithm to accelerate the fall detection system on based on a local adjustment of the velocity field.

Citation Download Citation

Mariem Gnouma, Ridha Ejbali, and Mourad Zaied "Human fall detection based on block matching and silhouette area", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034105 (17 March 2017); https://doi.org/10.1117/12.2268988

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