Person Re-identification in Frontal Gait Sequences via Histogram of Optic Flow Energy Image

In this work, we propose a novel methodology of re-identifying people in frontal video sequences, based on a spatio-temporal representation of the gait based on optic flow features, which we call Histogram Of Flow Energy Image (HOFEI). Optic Flow based methods do not require the silhouette computation thus avoiding image segmentation issues and enabling online re-identification (Re-ID) tasks. Not many works addressed Re-ID with optic flow features in frontal gait. Here, we conduct an extensive study on CASIA dataset, as well as its application in a realistic surveillance scenario- HDA Person dataset. Results show, for the first time, the feasibility of gait re-identification in frontal sequences, without the need for image segmentation.