Lateral inhibition in accumulative computation and fuzzy sets for human fall pattern recognition in colour and infrared imagery

Abstract

Fall detection is an emergent problem in pattern recognition. In this paper, a novel approach which enables to identify a type of a fall and reconstruct its characteristics is presented. The features detected include the position previous to a fall, the direction and velocity of a fall, and the postfall inactivity. Video sequences containing a possible fall are analysed image by image using the lateral inhibition in accumulative computation method. With this aim, the region of interest of human figures is examined in each image, and geometrical and kinematic characteristics for the sequence are calculated. The approach is valid in colour and in infrared video. © 2013 Antonio Fernández-Caballero et al.