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Person Re-identification Based on Adaptive Feature Selection

  • Wangyang Wei
  • Huadong Ma
  • Haitao Zhang
  • Yihong Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8351)

Abstract

In video surveillance, it is very important to identify individuals or determine whether a given individual has already appeared over a large-scale network of cameras, which is so called problem of person re-identification. In general, the human appearance obtained in one camera is usually different from others obtained in other cameras, because of variations in view angle, illumination, body poses, clothing, background clutter and occlusion. Thus, almost none of the existing methods of person re-identification can work with satisfied accuracy. In order to address this problem, we propose a person re-identification approach by using adaptive feature selection method. Specifically, at first, we detect human and human body parts. Then, we extract certain features on each part adaptively driven by their unique and inherent appearance attributes. At last, we map the person re-identification problem to a distance learning problem, and find out the similarity between corresponding body parts. The approach has been evaluated through extensive experiments, and the results show that our method can improve the accuracy of person re-identification greatly.

Keywords

Person Re-identification Adaptive Feature Selection Video Surveillance Part Based Models 

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References

  1. 1.
    Felzenszwalb, P., Girshick, R., McAllester, D., Ramanan, D.: Object Detection with Discriminatively Trained Part Based Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 1627–1645 (2010)CrossRefGoogle Scholar
  2. 2.
    Liu, C., Gong, S., Loy, C.C., Lin, X.: Person Re-identification: What Features Are Important? In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 391–401. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Hernandez, A., Reyes, M., Escalera, S., Radeva, P.: Spatio-Temporal Grabcut Human Segmentation for Face and Pose Recovery. In: CVPRW 2010, pp. 33–40 (2010)Google Scholar
  4. 4.
    Truong Cong, D., Khoudour, L., Achard, C., Meurie, C., Lezoray, O.: People re-identification by spectral classification of silhouettes. Signal Processing 90, 2362–2374 (2010)CrossRefzbMATHGoogle Scholar
  5. 5.
    Bedagkar-Gala, A., Shah, S.: Part-based spatio-temporal model for multi-person re-identification. Pattern Recognition Letters 33, 1908–1915 (2011)CrossRefGoogle Scholar
  6. 6.
    Bazzani, L., Cristani, M., Perina, A., Murino, V.: Multiple-shot person re-identification by chromatic and epitomic analyses. Pattern Recognition Letters 33, 898–903 (2012)CrossRefGoogle Scholar
  7. 7.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)CrossRefGoogle Scholar
  8. 8.
    Bak, S., Corvee, E., Brmond, F., Thonnat, M.: Person Re-identification Using Spatial Covariance Regions of Human Body Parts. In: The 7th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS 2010), pp. 435–440 (2010)Google Scholar
  9. 9.
    Mazzon, R., et al.: Person re-identification in crowd. Pattern Recognition Letters 33, 1828–1837 (2012)CrossRefGoogle Scholar
  10. 10.
    Li, P., Ma, H., Ming, A.: View-based 3D model retrieval using two-level spatial structure. In: IEEE ICIP 2011, pp. 3657–3660 (2011)Google Scholar
  11. 11.
    Farenzena, M., Bazzani, L., Perina, A., Murino, V., Cristani, M.: Person re-identification by symmetry-driven accumulation of local features. In: CVPR 2010, pp. 2360–2367 (2010)Google Scholar
  12. 12.
    Bak, S., Corvee, E., Brmond, F., Thonnat, M.: Person Re-identification Using Haar-based and DCD-based Signature. In: AVSS 2010, pp. 1–8 (2010)Google Scholar
  13. 13.
    Zheng, W.-S., Gong, S., Xiang, T.: Person re-identification by probabilis-tic relative distance comparison. In: CVPR 2011, pp. 649–656 (2011)Google Scholar
  14. 14.
    Doretto, G., Sebastian, T., Tu, P., Rittscher, J.: Appearance-based person re-identification in camera networks: Problem overview and current approaches. Journal of Ambient Intelligence and Humanized Computing 2, 127–151 (2011)CrossRefGoogle Scholar
  15. 15.
    Ming, A., Ma, H.: An Algorithm Testbed for the Biometrics Grid. In: Cérin, C., Li, K.-C. (eds.) GPC 2007. LNCS, vol. 4459, pp. 447–458. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  16. 16.
    Satta, R., Fumera, G., Roli, F.: Exploiting Dissimilarity Representations for Person Re-identification. In: Pelillo, M., Hancock, E.R. (eds.) SIMBAD 2011. LNCS, vol. 7005, pp. 275–289. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  17. 17.
    Baltieri, D., Vezzani, R., Cucchiara, R.: SARC3D: A New 3D Body Model for People Tracking and Re-identification. In: Maino, G., Foresti, G.L. (eds.) ICIAP 2011, Part I. LNCS, vol. 6978, pp. 197–206. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  18. 18.
    Bak,S., Corvee, E., Bremond, F., Thonnat, M.: Person re-identification using spatial covariance regions of human body parts. In: Proc. 7th IEEE Internat. Conf. on Advanced Video and Signal Based Surveillance (AVSS), pp.435-440, (2010). Google Scholar
  19. 19.
    de Oliveira, I., de Souza Pio, J.: Object re-identification in multiple cameras system. In: 4th Internat. Conf. on Embedded and Multimedia Computing (EMCom), pp. 1–8 (2009)Google Scholar
  20. 20.
    Prosser, B., Zheng, W., Gong, S., Xiang, T.: Person re-identification by support vector ranking. BMVC 2010, 1–11 (2010)Google Scholar
  21. 21.
    Zheng, W., Gong, S., Xiang, T.: Transfer Re-identification: From Person to Set-based Verification. In: CVPR 2012, pp. 2650–2657 (2012)Google Scholar
  22. 22.
    Satta, R., Fumera, G., Roli, F., Cristani, M., Murino, V.: A Multiple Component Matching Framework for Person Re-identification. In: Maino, G., Foresti, G.L. (eds.) ICIAP 2011, Part II. LNCS, vol. 6979, pp. 140–149. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  23. 23.
    Hirzer, M., Beleznai, C., Roth, P.M., Bischof, H.: Person Re-identification by Descriptive and Discriminative Classification. In: Heyden, A., Kahl, F. (eds.) SCIA 2011. LNCS, vol. 6688, pp. 91–102. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  24. 24.
    Schwartz, W.R., Davis, L.S.: Learning Discriminative Appearance-Based Models Using Partial Least Squares. In: Proceedings of the XXII Brazilian Symposium on Computer Graphics and Image Processing, pp. 11–14 (2009)Google Scholar
  25. 25.
    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)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Wangyang Wei
    • 1
  • Huadong Ma
    • 1
  • Haitao Zhang
    • 1
  • Yihong Gao
    • 1
  1. 1.Beijing Key Lab of Intelligent Telecommunications Software and MultimediaBeijing University of Posts and TelecommunicationsBeijingChina

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