In this paper, we present a person re-identification method based on appearance classification. It consists a human silhouette comparison by characterizing and classification of a persons appearance (the front and the back appearance) using the geometric distance between the detected head of person and the camera. The combination of head detector with an orthogonal iteration algorithm to help head pose estimation and appearance classification is the novelty of our work. In this way, the is achieved robustness against viewpoint, illumination and clothes appearance changes. Our approach uses matching of interest-points descriptors based on fast cross-bin metric. The approach applies to situations where the number of people varies continuously, considering multiple images for each individual. © 2011 Springer-Verlag.
CITATION STYLE
Aziz, K. E., Merad, D., & Fertil, B. (2011). Person re-identification using appearance classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6754 LNCS, pp. 170–179). https://doi.org/10.1007/978-3-642-21596-4_18
Mendeley helps you to discover research relevant for your work.