Color spaces and histogram distances influence on people re-identification in video stream

Abstract

The influence of color spaces and histogram distances on object re-identification in video stream is investigated. Dataset with images of pedestrians is being analyzed. A set of color spaces, histograms types and distance functions is applied to minimize re-identification errors by calculating false acceptance and false rejection error rates.