Entropy Measurement to Extract the Signification of Abnormal Activity from Camera’s Frames and its Application for Fall Detection

By Hoang Manh Ha, Tran Ba Minh Son, Nguyen Xuan Dung, Vo Quoc Thong
DOI: 10.37550/tdmu.EJS/2020.04.081

Abstract

Most of the indoor accidents are related with fall down. Many medical studies are point out that key factor for keeping patient’s life is fast response of monitoring system. In modern life, peoples are isolated with neighbor, especially in living quarters. Therefore many solutions are developed for falling down monitoring that base on wearable sensors. These methods require of an expensive sensors system with electric power supplier and telecommunication devices. In context of patients with disease and weak status, patients are trend to remove sensor system. This issue requires to find out another approach so that sensors system will not be needed. We study the fall detection by monitoring camera. For increase the accuracy, we proposed a simple and effective method to extract features of abnormal activities. By tracking the magnitude of entropy and its distribution, our fall detection model has a capability of differentiating falls from other activities

Keywords

feature extraction, fall monitoring, chaos of information, entropy

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