Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, Epiciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Conference papers

Multiple-shot Human Re-Identification by Mean Riemannian Covariance Grid

Abstract : Human re-identification is defined as a requirement to determine whether a given individual has already appeared over a network of cameras. This problem is particularly hard by significant appearance changes across different camera views. In order to re-identify people a human signature should handle difference in illumination, pose and camera parameters. We propose a new appearance model combining information from multiple images to obtain highly discriminative human signature, called Mean Riemannian Covariance Grid (MRCG). The method is evaluated and compared with the state of the art using benchmark video sequences from the ETHZ and the i-LIDS datasets. We demonstrate that the proposed approach outperforms state of the art methods. Finally, the results of our approach are shown on two other more pertinent datasets.
Complete list of metadata

Cited literature [20 references]  Display  Hide  Download
Contributor : Slawomir Bak Connect in order to contact the contributor
Submitted on : Wednesday, September 7, 2011 - 6:47:01 PM
Last modification on : Friday, February 4, 2022 - 3:22:17 AM
Long-term archiving on: : Tuesday, November 13, 2012 - 10:06:12 AM


Files produced by the author(s)


  • HAL Id : inria-00620496, version 1



Slawomir Bak, Etienne Corvee, François Bremond, Monique Thonnat. Multiple-shot Human Re-Identification by Mean Riemannian Covariance Grid. Advanced Video and Signal-Based Surveillance, Aug 2011, Klagenfurt, Austria. ⟨inria-00620496⟩



Record views


Files downloads