Camera Based Fall Detection Using Multiple Features Validated with Real Life Video

More than thirty percent of persons over 65 years fall at least once a year and are often not able to get up again unaided. The lack of timely aid can lead to severe complications such as dehydration, pressure ulcers and death. A camera based fall detection system can provide a solution. In this paper we compare four different fall features extracted from the dominant foreground object, as well as various combinations thereof. All tests are executed using real life data, which has been recorded at the home of 4 elderly, containing 24 falls. Experiments indicate that a fall detector based on a combination of aspect ratio, head speed and fall angle is preferred. The preliminary detector, which still has a substantial false alarm rate with a precision of 0.257(±0.073) and a promising recall of 0.896(±0.194), gives insights for further improvement as is discussed.Debard G., Karsmakers P., Deschodt M., Vlaeyen E., Van den Bergh J., Dejaeger E., Milisen K., Goedemé T., Tuytelaars T., Vanrumste B., ''Camera based fall detection using multiple features validated with real life video'', Workshop proceedings 7th international conference on intelligent environments - IE 2011, vol. 10, pp. 441-450, July 25-28, 2011, Nottingham, UK.status: publishe