Human action recognition using the motion of interest points

Even if the problem of human action categorization from videos has received a lot of attention during the past decade, it remains a challenging problem in operative conditions due to camera motion, occlusion, moving background, illumination changes and the variations of human appearance and postures. In this paper a new motion descriptor, based on a sparse optical flow computed by interest point tracking is presented. This motion descriptor is by design invariant to scale, camera motion and is not affected by non stationary background. The results of the recognition method are computed using a standard database and are compared to other approaches in literature.