Abstract
Person re-identification aims to match different persons observed in non-overlapping camera views. Researchers have proposed many person descriptors based on global or local descriptions, while both of them have achieved satisfying matching results, however, their ranking lists usually vary a lot for the same query person. These motivate us to investigate an approach to aggregate them to optimize the original matching results. In this paper, we proposed a coupled-view based ranking optimization method through cross KNN rank aggregation and graph-based re-ranking to revise the original ranking lists. Its core assumption is that the images of the same person should share the similar visual appearance in both global and local views. Extensive experiments on two datasets show the superiority of our proposed method with an average improvement of 20-30% over the state-of-the-art methods at CMC@1.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Gheissari, N., Sebastian, T.B., et al.: Person re-identification using spatiotemporal appearance. In: Computer Vision and Pattern Recognition (CVPR), pp. 1528–1535 (2006)
Gray, D., Tao, H.: Viewpoint invariant pedestrian recognition with an ensemble of localized features. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 262–275. Springer, Heidelberg (2008)
Farenzena, M., Bazzani, L., Perina, A., et al.: Person re-identification by symmetry-driven accumulation of local features. In: Computer Vision and Pattern Recognition (CVPR), pp. 2360–2367 (2010)
Zheng, W.S., Gong, S., Xiang, T.: Person re-identification by probabilistic relative distance comparison. In: Computer Vision and Pattern Recognition (CVPR), pp. 649–656 (2011)
Kostinger, M., Hirzer, M., Wohlhart, P., et al.: Large scale metric learning from equivalence constraints. In: Computer Vision and Pattern Recognition (CVPR), pp. 2288–2295 (2012)
Mignon, A., Jurie, F.: PCCA: A new approach for distance learning from sparse pairwise constraints. In: Computer Vision and Pattern Recognition (CVPR), pp. 2666–2672 (2012)
Zhao, R., Ouyang, W., Wang, X.: Unsupervised salience learning for person re-identification. In: Computer Vision and Pattern Recognition (CVPR), pp. 3586–3593 (2013)
Xu, Y., Lin, L., Zheng, W.S., et al.: Human re-identification by matching compositional template with cluster sampling. In: International Conference on Computer Vision (ICCV), pp. 3152–3159 (2013)
Javed, O., Shafique, K., Shah, M.: Appearance modeling for tracking in multiple non-overlapping cameras. In: Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 26–33 (2005)
Wang, X., Doretto, G., Sebastian, T., et al.: Shape and appearance context modeling. In: International Conference on Computer Vision (ICCV), pp. 1–8 (2007)
Hirzer, M., Roth, P.M., Köstinger, M., Bischof, H.: Relaxed pairwise learned metric for person re-identification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part VI. LNCS, vol. 7577, pp. 780–793. Springer, Heidelberg (2012)
Ma, B., Su, Y., Jurie, F.: Local descriptors encoded by fisher vectors for person re-identification. In: European Conference on Computer Vision Workshops and Demonstrations (ECCV Workshop), pp. 413–422 (2012)
Leng, Q., Hu, R., Liang, C., et al.: Bidirectional ranking for person re-identification. In: International Conference on Multimedia and Expo (ICME), pp. 1–6 (2013)
Liu, C., Loy, C.C., Gong, S., et al.: POP: Person re-identification post-rank optimisation. In: International Conference on Computer Vision (ICCV), pp. 441–448 (2013)
An, L., Chen, X., Kafai, M., et al.: Improving person re-identification by soft biometrics based reranking. In: International Conference on Distributed Smart Cameras (ICDSC), pp. 1–6 (2013)
Leng, Q., Hu, R., Liang, C., et al.: Person re-identification with content and context re-ranking. In: Multimedia Tools and Applications, pp. 1–26 (2014)
Ali, S., Javed, O., Haering, N., et al.: Interactive retrieval of targets for wide area surveillance. In: International Conference on Multimedia (MM), pp. 895–898 (2010)
Hirzer, M., Beleznai, C., Roth, P.M., et al.: Person re-identification by descriptive and discriminative classification. In: Image Analysis (IA), pp. 91–102 (2011)
Zhao, R., Ouyang, W., Wang, X.: Person re-identification by salience matching. In: International Conference on Computer Vision (ICCV), pp. 2528–2535 (2013)
Zhang, S., Yang, M., Cour, T., et al.: Query specific fusion for image retrieval. In: European Conference on Computer Vision(ECCV), pp. 660–673 (2012)
Gray, D., Brennan, S., Tao, H.: Evaluating appearance models for recognition, reacquisition, and tracking. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (2007)
Li, W., Wang, X.: Locally aligned feature transforms across views. In: Computer Vision and Pattern Recognition (CVPR), pp. 3594–3601 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ye, M., Chen, J., Leng, Q., Liang, C., Wang, Z., Sun, K. (2015). Coupled-View Based Ranking Optimization for Person Re-identification. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8935. Springer, Cham. https://doi.org/10.1007/978-3-319-14445-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-14445-0_10
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14444-3
Online ISBN: 978-3-319-14445-0
eBook Packages: Computer ScienceComputer Science (R0)