TED: A texture-edge descriptor for pedestrian detection in video sequences

This paper presents a novel descriptor, TED, for pedestrian detection in video sequences. TED describes texture and edge information simultaneously. TED is a local descriptor because it is defined over a neighborhood. The size of the TED, independent of the neighborhood size defined over it, is 8 bits. TED is based on intensity difference, and so it is robust against illumination changes. We demonstrate TED performance in a block-based framework for pedestrian detection. Experimental results show the effectiveness of the proposed descriptor when applied in different outdoor and indoor environments.

► TED is a novel descriptor for pedestrian detection in video sequences. ► TED is a local descriptor, which describes texture and edge information simultaneously. ► Size of the TED, independent of the neighborhood size defined over it, is 8 bits. ► TED is based on intensity difference, and so it is robust against illumination changes. ► The effectiveness of our descriptor is demonstrated in different environments.