Learning mid-level motion features for the recognition of body movements

Abstract

Robust Recognition of Body Movements based on Critical Mid-Level Features • Humans can recognize body movements (e.g. walking and running) accurately and robustly. • This robustness is demonstrated by the ability of subjects to recognize body movements from strongly impoverished stimuli, like Point-like walkers (PLW), which consist only of a small number of illuminated dots that move like the joints of a human actor [6]. Subjects can even recognize gender, emotions, and identity from these stimuli. • A possible explanation for this robust generalization is that the brain extracts specific motion features (of intermediate complexity) that are shared by both stimuli classes (normal walker and PLW). • The nature of these features is unknown, and it has been discussed whether they are based predominantly on motion or form information [7]. In a recent study, combining methods from image statistics and psychophysical experiments, it was shown that robust recognition can be accomplished based on mid-level motion features [2]. Supported by National Institute of Health grant 2R01-EY-07861-11, Volkswagenstiftung, DFG and HFSP.