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The population of senior citizens is continuously increasing, and most of them are living alone at home. The fall is main cause to make severe injury or mortality. The fall detection systems turn into equipment to help elderly rapidly. A technology to detect fall based on vision systems offers a new promising solution to analyze human behavior and detect fall events. In this paper, we propose a new method to detect falls in a video sequence. In our proposed system, the Maximum Euclidean Distance was used for human motion analysis. Then the fall posture of human is detected by using the approximated ellipse method. Our algorithm provides promising results on video sequences of daily activities taken by IP camera installed on a high position like bird’s eye view and simulated falls with occlusions. Keywords—Fall detection, Shape Context Matching, Euclidean distance.

Human Fall Detection using Maximum Euclidean Distance and Ellipse Approximation