Automatic fall incident detection in compressed video for intelligent homecare

Abstract

This paper presents a compressed-domain fall incident detection scheme for intelligent homecare applications. First, a compressed-domain object segmentation scheme is performed to extract moving objects based on global motion estimation and local motion clustering. After detecting the moving objects, three compressed-domain features of each object are then extracted for identifying and locating fall incidents. The proposed system can differentiate fall-down from squatting by taking into account the event duration. Our experiments show that the proposed method can correctly detect fall incidents in real time.