Video-surveillance and context aware system for activity recognition

Fall detection is the main issue in design an AAL system for elderly. This paper describes an algorithm for vision and audio fall detection. The main problem with video surveillance is the distinction of a fall from similar daily activities such as lying down, kneeling, standing up, walking or falling. The goal of this research is to design a reliable fall detection system which not only relies on video analysis, but also uses the information from environment of the patient to create context information.

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