A new pedestrian detection descriptor based on the use of spatial recurrences

Abstract

Recent work on pedestrian detection has relied on the concept of local co-occurences of features to propose higher-order, richer descriptors. While this idea has proven to be benefitial for this detection task, it fails to properly account for a more general and/or holistic representation. In this paper, a novel, flexible, and modular descriptor is proposed which is based on the alternative concept of visual recurrence and, in particular, on a mathematically sound tool, the recurrence plot. The experimental work conducted provides evidence on the discriminatory power of the descriptor, with results comparable to recent similar approaches. Furthermore, since its degree of locality, its visual compactness, and the pair-wise feature similarity can be easily changed, it holds promise to account for characterizations of other descriptors, as well as for a range of accuracy-computational trade-offs for pedestrian detection and, possibly, also for other object detection problems.