Real-time Motion Template Gradients using Intel CVLib

In this paper, we present an extension to the real-time motion template research for computer vision as previously developed in (Davis 1997). The underlying representation is a Motion History Image (MHI) that temporally layers consecutive image silhouettes (or motion properties) of a moving person into a single template form. Originally a global, label-based method was used for recognition. In this work, we construct a more localized motion characterization for the MHI that extracts motion orientations in real-time. Basically, directional motion information can be recovered directly from the intensity gradients within the MHI. In addition, we provide a few simple motion features using these orientations. The approach presented is implemented in real-time on a standard PC platform employing optimized routines, developed in part for this research, from the Intel® Computer Vision Library (CVLib). We conclude with an overview of this library and also a performance evaluation in terms of this research.