Detecting falls at homes using a network of low-resolution cameras

In a smart home system, a camera-based fall detector at elderly homes leads to immediate alarming and helping. In this paper we propose an approach for the detection of falls based on multiple cameras. Based on semantic driven features, fall detection is done in 3D and fuzzy logic is used to estimate confidence values for different human postures as well as for the incidence of a fall/no fall. Emphasis is given on simplicity, low computational effort and fast processing. Therefore, based on an evaluation on 73 test sequences, we show the applicability of the method for videos with low spatial resolution and frame rate.