Person Re-identification by Discriminatively Selecting Parts and Features

This paper presents a novel appearance-based method for person re-identification. The core idea is to rank and select different body parts on the basis of the discriminating power of their characteristic features. In our approach, we first segment the pedestrian images into meaningful parts, then we extract features from such parts as well as from the whole body and finally, we perform a salience analysis based on regression coefficients. Given a set of individuals, our method is able to estimate the different importance (or salience) of each body part automatically. To prove the effectiveness of our approach, we considered two standard datasets and we demonstrated through an exhaustive experimental section how our method improves significantly upon existing approaches, especially in multiple-shot scenarios.