Optimised spatio-temporal descriptors for real-time fall detection : comparison of SVM and Adaboost based classification

International audience; We propose a supervised approach to detect falls in home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing to evaluate fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual tr…