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Person Re-identification by Articulated Appearance Matching

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Book cover Person Re-Identification

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Re-identification of pedestrians in video-surveillance settings can be effectively approached by treating each human figure as an articulated body, whose pose is estimated through the framework of Pictorial Structures (PS). In this way, we can focus selectively on similarities between the appearance of body parts to recognize a previously seen individual. In fact, this strategy resembles what humans employ to solve the same task in the absence of facial details or other reliable biometric information. Based on these insights, we show how to perform single image re-identification by matching signatures coming from articulated appearances, and how to strengthen this process in multi-shot re-identification by using Custom Pictorial Structures (CPS) to produce improved body localizations and appearance signatures. Moreover, we provide a complete and detailed breakdown-analysis of the system that surrounds these core procedures, with several novel arrangements devised for efficiency and flexibility. Finally, we test our approach on several public benchmarks, obtaining convincing results.

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Notes

  1. 1.

    http://phoenix.ics.uci.edu/software/pose/

  2. 2.

    http://pascal.inrialpes.fr/data/human/

  3. 3.

    http://www.umiacs.umd.edu/~schwartz/datasets.html

  4. 4.

    Available at http://www.re-identification.net/.

  5. 5.

    Available at http://san.hufs.ac.kr/~chengds/software.html.

References

  1. Andriluka, M., Roth, S., Schiele, B.: Pictorial structures revisited: people detection and articulated pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1014–1021 (2009)

    Google Scholar 

  2. Bak, S., Charpiat, G., Corvee, E., Bremond, F., Thonnat, M.: Learning to match appearances by correlations in a covariance metric space. In: European Conference on Computer Vision, pp. 806–820 (2012)

    Google Scholar 

  3. Bak, S., Corvee, E., Bremond, F., Thonnat, M.: Person re-identification using haar-based and DCD-based Signature. In: 2nd Workshop on Activity Monitoring by Multi-Camera Surveillance Systems (2010)

    Google Scholar 

  4. Bak, S., Corvee, E., Bremond, F., Thonnat, M.: Person re-identification using spatial covariance regions of human body parts. In: 7th IEEE International Conference on Advanced Video and Signal-Based Surveillance (2010)

    Google Scholar 

  5. Bak, S., Corvee, E., Bremond, F., Thonnat, M.: Multiple-shot human re-identification by mean riemannian covariance grid. In: 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, pp. 179–184 (2011)

    Google Scholar 

  6. Barbosa, I.B., Cristani, M., Del Bue, A., Bazzani, L., Murino, V.: Re-identification with rgb-d sensors. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) European Conference on Computer Vision: Workshops and Demonstrations. Lecture Notes in Computer Science, vol. 7583, pp. 433–442. Springer, Berlin, Heidelberg (2012)

    Google Scholar 

  7. Bazzani, L., Cristani, M., Murino, V.: Symmetry-driven accumulation of local features for human characterization and re-identification. Comput. Vis. Image Underst. 117(2), 130–144 (2013)

    Google Scholar 

  8. Bazzani, L., Cristani, M., Perina, A., Murino, V.: Multiple-shot person re-identification by chromatic and epitomic analyses. Pattern Recogn. Lett. 33(7), 898–903 (2012)

    Article  Google Scholar 

  9. Cheng, D.S., Cristani, M., Stoppa, M., Bazzani, L., Murino, V.: Custom pictorial structures for re-identification. In: British Machine Vision Conference, pp. 1–11 (2011)

    Google Scholar 

  10. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 886–893 (2005)

    Google Scholar 

  11. Doretto, G., Sebastian, T., Tu, P., Rittscher, J.: Appearance-based person reidentification in camera networks: problem overview and current approaches. J. Ambient Intell. Hum. Comput. 2(2), 127–151 (2011)

    Article  Google Scholar 

  12. Eichner, M., Ferrari, V.: Better appearance models for pictorial structures. In: British Machine Vision Conference (2009)

    Google Scholar 

  13. Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge 2010 (VOC2010) Results (2010)

    Google Scholar 

  14. Farenzena, M., Bazzani, L., Perina, A., Murino, V., Cristani, M.: Person re-Identification by symmetry-driven accumulation of local features. In: IEEE Conference on Computer Vision and Pattern Recognition (2010)

    Google Scholar 

  15. Felzenszwalb, P.F., Girshick, R.B., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part-based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627–1645 (2010)

    Article  Google Scholar 

  16. Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial structures for object recognition. Int. J. Comput. Vision 61(1), 55–79 (2005)

    Article  Google Scholar 

  17. Figueira, D., Bazzani, L., Minh, H., Cristani, M., Bernardino, A., Murino, V.: Semi-supervised multi-feature learning for person re-identification. In: International Conference on Advanced Video and Signal-Based Surveillance (2013)

    Google Scholar 

  18. Forssén, P.E.: Maximally stable colour regions for recognition and matching. In: IEEE Conference on Computer Vision and Pattern Recognition (2007)

    Google Scholar 

  19. Freund, Y., Schapire, R.: A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 55(1), 119–139 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  20. Gheissari, N., Sebastian, T.B., Tu, P.H., Rittscher, J., Hartley, R.: Person reidentification using spatiotemporal appearance. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 1528–1535 (2006)

    Google Scholar 

  21. Gray, D., Brennan, S., Tao, H.: Evaluating appearance models for recognition, reacquisition and tracking. In: IEEE International Workshop on Performance Evaluation for Tracking and Surveillance (2007)

    Google Scholar 

  22. Gray, D., Tao, H.: Viewpoint invariant pedestrian recognition with an ensamble of localized features. In: European Conference on Computer Vision, pp. 262–275 (2008)

    Google Scholar 

  23. Hamdoun, O., Moutarde, F., Stanciulescu, B., Steux, B.: Person re-identification in multi-camera system by signature based on interest point descriptors collected on short video sequences. In: ACM/IEEE International Conference on Distributed Smart Cameras, pp. 1–6 (2008)

    Google Scholar 

  24. Hariharan, B., Malik, J., Ramanan, D.: Discriminative decorrelation for clustering and classification. In: European Conference on Computer Vision, pp. 459–472 (2012)

    Google Scholar 

  25. Lin, Z., Davis, L.: Learning pairwise dissimilarity profiles for appearance recognition in visual surveillance. In: 4th International Symposium on Advances in Visual Computing (2008)

    Google Scholar 

  26. Minh, H.Q., Bazzani, L., Murino, V.: A unifying framework for vector-valued manifold regularization and multi-view learning. In: 30th International Conference on Machine Learning (2013)

    Google Scholar 

  27. Platt, J.: Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Adv. Large Margin Classif. 10(3), 61–74 (1999)

    Google Scholar 

  28. Prosser, B., Zheng, W., Gong, S., Xiang, T.: Person re-identification by support vector ranking. In: British Machine Vision Conference (2010)

    Google Scholar 

  29. Ramanan, D.: Learning to parse images of articulated bodies. In: Advances in Neural Information Processing Systems, pp. 1129–1136 (2007)

    Google Scholar 

  30. Ramanan, D., Forsyth, D.A., Zisserman, A.: Tracking people by learning their appearance. IEEE Trans. Pattern Anal. Mach. Intell. 29(1), 65–81 (2007)

    Google Scholar 

  31. Salvagnini, P., Bazzani, L., Cristani, M., Murino, V.: Person re-identification with a ptz camera: an introductory study. In: IEEE International Conference on Image Processing (2013)

    Google Scholar 

  32. Satta, R., Fumera, G., Roli, F., Cristani, M., Murino, V.: A multiple component matching framework for person re-identification. In: 16th International Conference on Image Analysis and Processing, ICIAP’11, pp. 140–149. Springer-Verlag, Berlin, Heidelberg. http://dl.acm.org/citation.cfm?id=2042703.2042719 (2011)

  33. Schwartz, W., Davis, L.: Learning discriminative appearance-based models using partial least squares. In: XXII SIBGRAPI 2009 (2009)

    Google Scholar 

  34. Shapire, R., Freund, Y., Bartlett, P., Lee, W.: Boosting the margin: a new explanation for the effectiveness of voting methods. Ann. Stat. 26(5), 1651–1686 (1998)

    Article  Google Scholar 

  35. Sivic, J., Zitnick, C.L., Szeliski, R.: Finding people in repeated shots of the same scene. In: British Machine Vision Conference (2006)

    Google Scholar 

  36. Wang, X., Doretto, G., Sebastian, T.B., Rittscher, J., Tu, P.H.: Shape and appearance context modeling. In: IEEE International Conference on Computer Vision, pp. 1–8 (2007)

    Google Scholar 

  37. Wang, X., Han, T.X., Yan, S.: An hog-lbp human detector with partial occlusion handling. In: IEEE International Conference on Computer Vision, pp. 32–39 (2009)

    Google Scholar 

  38. Yang, Y., Ramanan, D.: Articulated human detection with flexible mixtures-of-parts. IEEE Trans. Pattern Anal. Mach. Intell. PP(99), 1–1 (2012)

    Google Scholar 

  39. Zheng, W., Gong, S., Xiang, T.: Associating groups of people. In: British Machine Vision Conference (2009)

    Google Scholar 

  40. Zheng, W.S., Gong, S., Xiang, T.: Reidentification by relative distance comparison. IEEE Trans. Pattern Anal. Mach. Intell. 35(3), 0653–668 (2013)

    Google Scholar 

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Acknowledgments

This work was supported by Hankuk University of Foreign Studies Research Fund of 2013.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Hankuk University of Foreign Studies, 81, Oedae-ro, Mohyeon-myeon, Cheoin-gu, Yongin-si, Gyeonggi-do, 449-791, South Korea

    Dong Seon Cheng

  2. Department of Computer Science, University of Verona, Ca’ Vignal 2, Verona, 37134, Italy

    Marco Cristani

Authors
  1. Dong Seon Cheng
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  2. Marco Cristani
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Correspondence to Dong Seon Cheng .

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Editors and Affiliations

  1. Queen Mary University, London, United Kingdom

    Shaogang Gong

  2. University of Verona, Italy

    Marco Cristani

  3. National University of Singapore, Singapore

    Shuicheng Yan

  4. The Chinese University of Hong Kong, Shatin, Hong Kong SAR

    Chen Change Loy

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Cheng, D.S., Cristani, M. (2014). Person Re-identification by Articulated Appearance Matching. In: Gong, S., Cristani, M., Yan, S., Loy, C. (eds) Person Re-Identification. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6296-4_7

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  • DOI: https://doi.org/10.1007/978-1-4471-6296-4_7

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6295-7

  • Online ISBN: 978-1-4471-6296-4

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