Monocular pedestrian recognition using motion parallax

This paper presents a novel focus-of-attention strategy for monocular pedestrian recognition. It uses Bayes' rule to estimate the posterior for the presence of a pedestrian in a certain (rectangular) image region, based on motion parallax features. This posterior is used as a parameter to control the amount of regions of interest (ROIs) that is passed to subsequent verification stages. For the latter, we use a state-of- the-art pedestrian recognition scheme which consists of multiple modules in a cascade architecture. We obtain optimized settings for the control parameters of the combined cascade system by a sequential ROC convex hull technique. Experiments are conducted on image data captured from a moving vehicle in an urban environment. We demonstrate that the proposed focus-of-attention strategy reduces the false positives of an otherwise identical monocular pedestrian recognition system by a factor of two, at equal detection rates. The overall system maintains processing rates close to real-time.