Towards Fully Automated Person Re-identification

Matteo Taiana, Dario Figueira, Athira Nambiar, Jacinto Nascimento, Alexandre Bernardino

Abstract

In this work we propose an architecture for fully automated person re-identification in camera networks. Most works on re-identification operate with manually cropped images both for the gallery (training) and the probe (test) set. However, in a fully automated system, re-identification algorithms must work in series with person detection algorithms, whose output may contain false positives, detections of partially occluded people and detections with bounding boxes misaligned to the people. These effects, when left untreated, may significantly jeopardise the performance of the re-identification system. To tackle this problem we propose modifications to classical person detection and re-identification algorithms, which enable the full system to deal with occlusions and false positives. We show the advantages of the proposed method on a fully labelled video data set acquired by 8 high-resolution cameras in a typical office scenario at working hours.

References

  1. Andriluka, M., Roth, S., and Schiele, B. (2009). Pictorial Structures Revisited: People Detection and Articulated Pose Estimation. CVPR.
  2. Bak, S., Corvée, E., Brémond, F., and Thonnat, M. (2012). Boosted human re-identification using Riemannian manifolds. ImaVis.
  3. Cheng, D. S., Cristani, M., Stoppa, M., Bazzani, L., and Murino, V. (2011). Custom pictorial structures for reidentification. In BMVC.
  4. Corvee, E., Bak, S., and Bremond, F. (2012). People detection and re-identification for multi surveillance cameras. VISAPP.
  5. Dikmen, M., Akbas, E., Huang, T., and Ahuja, N. (2011). Pedestrian recognition with a learned metric. In ACCV.
  6. Dollár, P., Belongie, S., and Perona, P. (2010). The Fastest Pedestrian Detector in the West. BMVC.
  7. Ess, A., Leibe, B., and Van Gool, L. (2007). Depth and Appearance for Mobile Scene Analysis. ICCV.
  8. Everingham, M., Van Gool, L., Williams, C., Winn, J., and Zisserman, A. (2010). The Pascal visual object classes (VOC) challenge. IJCV.
  9. Farenzena, M., Bazzani, L., Perina, A., Murino, V., and Cristani, M. (2010). Person re-identification by symmetry-driven accumulation of local features. In CVPR.
  10. Figueira, D., Bazzani, L., Minh, H. Q., Cristani, M., Bernardino, A., and Murino, V. (2013). Semisupervised multi-feature learning for person reidentification. AVSS.
  11. Gheissari, N., Sebastian, T., and Hartley, R. (2006). Person reidentification using spatiotemporal appearance. In CVPR.
  12. Girshick, R., Felzenszwalb, P., and McAllester, D. (2011). Object detection with grammar models. PAMI.
  13. Gray, D. and Tao, H. (2008). Viewpoint invariant pedestrian recognition with an ensemble of localized features. In ECCV.
  14. Hamdoun, O., Moutarde, F., Stanciulescu, B., and Steux., B. (2008). Person re-identification in multi-camera system by signature based on interest point descriptors collected on short video sequences. In ICDSC.
  15. Harandi, M. T., Sanderson, C., Wiliem, A., and Lovell, B. C. (2012). Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures. In WACV.
  16. Hirzer, M., Roth, P., Kostinger, M., and Bischof, H. (2012). Relaxed pairwise learned metric for person re-identification. In ECCV.
  17. Jungling, K., Bodensteiner, C., and Arens, M. (2011). Person re-identification in multi-camera networks. In CVPRW.
  18. Li, W. and Wang, X. (2013). Locally aligned feature transforms across views. In CVPR.
  19. Li, W., Zhao, R., and Wang, X. (2012). Human reidentification with transferred metric learning. In ACCV.
  20. Liu, C., Gong, S., Loy, C., and Lin, X. (2012a). Person reidentification: What features are important? In ECCV.
  21. Liu, C., Wang, G., Lin, X., and Li, L. (2012b). Person reidentification by spatial pyramid color representation and local region matching. IEICE.
  22. Ma, B., Su, Y., and Jurie., F. (2012). Bicov: a novel image representation for person re-identification and face verification. In BMVC.
  23. Mignon, A. and Jurie, F. (2012). Pcca: A new approach for distance learning from sparse pairwise constraints. In CVPR.
  24. Mogelmose, A., Bahnsen, C., and Moeslung, T. B. (2013a). Tri-modal person re-identification with RGB, depth and thermal features. In IEEE WPBVS.
  25. Mogelmose, A., Moeslund, T. B., and Nasrollahi, K. (2013b). Multimodal person re-identification using RGB-D sensors and a transient identification database. In IWBF.
  26. Pedagadi, S., Orwell, J., Velastin, S., and Boghossian, B. (2013). Local fisher discriminant analysis for pedestrian re-identification. In CVPR.
  27. Prosser, B., Zheng, W., Gong, S., Xiang, T., and Mary., Q. (2010). Person re-identification by support vector ranking. In BMCV.
  28. Quang, M. H., Bazzani, L., and Murino, V. (2013). A unifying framework for vector-valued manifold regularization and multi-view learning. In ICML.
  29. Taiana, M., Nascimento, J., and Bernardino, A. (2013). An improved labelling for the INRIA person data set for pedestrian detection. IbPRIA.
  30. Wang, X., Doretto, G., Sebastian, T., Rittscher, J., and Tu, P. (2007). Shape and appearance context modeling. In ICCV.
  31. Wu, Y., Mukunoki, M., Funatomi, T., Minoh, M., and Lao, S. (2011). Optimizing mean reciprocal rank for person re-identification. In AVSS.
  32. Zheng, W., Gong, S., and Xiang, T. (2009). Associating groups of people. In BMVC.
  33. Zheng, W., Gong, S., and Xiang, T. (2011). Person reidentification by probabilistic relative distance comparison. In CVPR.
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Paper Citation


in Harvard Style

Taiana M., Figueira D., Nambiar A., Nascimento J. and Bernardino A. (2014). Towards Fully Automated Person Re-identification . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 140-147. DOI: 10.5220/0004682301400147


in Bibtex Style

@conference{visapp14,
author={Matteo Taiana and Dario Figueira and Athira Nambiar and Jacinto Nascimento and Alexandre Bernardino},
title={Towards Fully Automated Person Re-identification},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={140-147},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004682301400147},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Towards Fully Automated Person Re-identification
SN - 978-989-758-009-3
AU - Taiana M.
AU - Figueira D.
AU - Nambiar A.
AU - Nascimento J.
AU - Bernardino A.
PY - 2014
SP - 140
EP - 147
DO - 10.5220/0004682301400147