Histogram of oriented gradients and region covariance descriptor in hierarchical feature-distribution scheme

Hierarchical feature-distribution scheme is a recently proposed framework for distribution of features in visual-sensor networks. It is intended for tasks, where one needs to establish a correspondence between two objects, seen by different cameras at different occasions. In visual-sensor networks, such pair of cameras may be very distant in network terms. Therefore, the hierarchical scheme results in significant reduction of network traffic, compared to naive approaches, which rely on flooding. In this paper we explore the performance of two state-of-the-art feature descriptors (histogram of oriented gradients and region covariance descriptor) in such featuredistribution scheme. Both methods are compared inthe terms of network load on the COIL-100 data set. Results show that even state-of-the-art feature descriptors benefit from hierarchical feature-distribution scheme.