Human fall detection based on block matching and silhouette area
Mariem Gnouma, Ridha Ejbali, Mourad Zaied · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2017
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.