Video Analytic for Fall Detection from Shape Features and Motion Gradients

Unintentional falls are common causes of serious injuries and health threats to patients as well as senior citizens living alone. Advanced computer vision algorithms and low cost cameras can be used for assessment of health hazards such as falls. In this paper, we propose a new approach to deal with this particular problem i.e. to detect unintentional falls, which are one of the greatest risks for seniors living alone. Our proposed approach is based on a combination of motion gradients and human shape features variation. Our proposed system provides promising results on video sequences of simulated falls.