Skip to main content
SpringerLink
Log in

Single-Shot Person Re-identification by Spectral Matching of Symmetry-Driven Local Features

  • Chapter
  • First Online:
Advanced Computing and Systems for Security

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 567))

  • 445 Accesses

Abstract

This paper presents an appearance-based approach for person re-identification. It comprises the extraction of features that models the significant prospects of human appearance: local patterns of the regions and the presence of the spatial distribution of color, texture with high informative patches. This information is extracted from different body parts by following the symmetry-asymmetry precept and combined to form the signature of an individual. In this way, the signatures provide robustness against illumination variation, arbitrary pose changes, and occlusion. Further, these signatures are utilized for the process of re-identification through the spectral matching scheme. The approach applies to a situation where single image per individual is available. Extensive experiments are carried out on challenging datasets to validate the performance of proposed model over the state-of-the-art.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Saghafi, M.A., Hussain, A., Zaman, H.B., Saad, M.H.: Review of person re-identification techniques. IET Comput. Vis. 8(6), 455–474 (2014)

    Article  Google Scholar 

  2. 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, pp. 2360–2367 (2010)

    Google Scholar 

  3. Schwartz, W., Davis, L.: Learning discriminative appearance-based models using partial least squares. In: The 22nd Brazilian Symposium on Computer Graphics and Image Processing, pp. 322–329 (2009)

    Google Scholar 

  4. Hirzer, M., Roth, P., Ostinger, M.K., Bischof, H.: Relaxed pairwise learned metric for person reidentification. In: Computer Vision-ECCV, pp. 780–793 (2012)

    Google Scholar 

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

    Google Scholar 

  6. Gray, D., Tao, H.: Viewpoint invariant pedestrian recognition with an ensemble of localized features. In: Computer Vision–ECCV, pp. 262–275 (2008)

    Google Scholar 

  7. Bak, S., Corvee, E., Bremond, F., Thonnat, M.: Boosted human re-identification using riemannian manifolds. Image Vis. Comput. 30(6), 443–452 (2012)

    Article  Google Scholar 

  8. Javed, O., Shafique, K., Rasheed, Z., Shah, M.: Modeling inter-camera space-time and appearance relationships for tracking accross non-overlapping views. CVIU Elsevier 109(2), 146–162 (2008)

    Google Scholar 

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

    Google Scholar 

  10. Zhao, R., Ouyang, W., Wang, X.: Unsupervised salience learning for person re-identification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3586–3593 (2013)

    Google Scholar 

  11. Zheng, W.S., Gong, S., Xiang, T.: Reidentification by relative distance comparison. IEEE Trans. Pattern Anal. Mach. Intell. 35(3), 653–668 (2013)

    Article  Google Scholar 

  12. Mignon, A., Jurie, F.: Pcca: A new approach for distance learning from sparse pairwise constraints. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2666–2672 (2012)

    Google Scholar 

  13. Li, W., Zhao, R., Wang, X.: Human reidentification with transferred metric learning. In: Computer Vision-ACCV, vol. 2012, pp. 31–44 (2013)

    Google Scholar 

  14. Dikmen, M., Akbas, E., Huang, T.S., Ahuja, N.: Pedestrian recognition with a learned metric. In: Computer Vision-ACCV, vol. 2010, pp. 501–512 (2011)

    Google Scholar 

  15. Wu, Y., Minoh, M., Mukunoki, M., Lao, S.: Set based discriminative ranking for recognition. In: Computer Vision-ECCV, vol. 2012, pp. 497–510 (2012)

    Google Scholar 

  16. Satta, R., Fumera, G., Roli, F., Cristani, M., Murino, V.: A multiple component matching framework for person re-identification. In: Image Analysis and Processing-ICIAP, pp. 140–149 (2011)

    Google Scholar 

  17. Cheng, D.S., Cristani, M., Stoppa, M., Bazzani, L., Murino, V.: Custom pictorial structures for re-identification. In: BMVC, vol. 2, issue no. 5 (2011)

    Google Scholar 

  18. Wang, X., Zhao, R.: Person Re-identification: System Design and Evaluation Overview, vol. 2, pp. 351–370. Springer (2014)

    Google Scholar 

  19. 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: Second ACM/IEEE International Conference on Distributed Smart Cameras, 2008. ICDSC 2008, pp. 1–6 (2008)

    Google Scholar 

  20. Yang, Y., Yang, J., Yan, J., Liao, S., Yi, D., Li, S.Z.: Salient color names for person re-identification. In: Computer Vision–ECCV 2014, pp. 536–551. Springer (2014)

    Google Scholar 

  21. Zhao, R., Ouyang, W., Wang, X.: Learning mid-level filters for person re-identification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 144–151. IEEE (2014)

    Google Scholar 

  22. Martinel, Niki, Micheloni, Christian, Foresti, Gian Luca: Kernelized saliency-based person re-identification through multiple metric learning. IEEE Trans. Image Process. 24(12), 5645–5658 (2015)

    Article  MathSciNet  Google Scholar 

  23. Jojic, N., Perina, A., Cristani, M., Murino, V., Frey, B.: Stel component analysis: Modeling spatial correlations in image class structure. In: IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009, vol. 30, issue no. 6, pp. 2044–2051

    Google Scholar 

  24. Sande, K.V.D., Gevers, T., Snoek, C.G.: Evaluating color descriptors for object and scene recognition. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1582–1596 (2010)

    Article  Google Scholar 

  25. Tuzel, O., Porikli, F., Meer, P.: Region covariance: a fast descriptor for detection and classification. In: Proceedings of the 9th European Conference on Computer Vision (ECCV), pp. 586–3593 (2006)

    Google Scholar 

  26. Nanda, A., Sa, P.K., Majhi, B.: Covarinace based person re-identification using spectral matching. In: INDICON (2014)

    Google Scholar 

  27. Nixon, M., Aguado, A.: Feature Extraction & Image Processing. Academic Press (2008)

    Google Scholar 

  28. Pennec, X., Fillard, P., Ayache, N.: A riemannian framework for tensor computing. Int. J. Comput. Vis., 41–66 (2006)

    Google Scholar 

  29. Leordeanu, M., Hebert, M.: A spectral technique for correspondence problems using pairwise constraints. In: Proceedings of 10th IEEE International Conference on Computer Vision (ICCV), pp. 1482–1489 (2005)

    Google Scholar 

  30. Prosser, B., Zheng, W.S., Gong, S., Xiang, T.: Person re-identification by support vector ranking. In: British Machine Vision Conference, vol. 2, issue no. 5, pp. 21.1–21.11 (2010)

    Google Scholar 

Download references

Acknowledgements

This work is supported by Grant Number SB/FTP/ETA-0059/2014 by Science and Engineering Research Board (SERB), Department of Science & Technology, Government of India.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India

    Aparajita Nanda & Pankaj K. Sa

Authors
  1. Aparajita Nanda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pankaj K. Sa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aparajita Nanda .

Editor information

Editors and Affiliations

  1. A.K. Choudhury School of Information Tec, Associate Prof., University of Calcutta A.K. Choudhury School of Information Tec, Kolkata, West Bengal, India

    Rituparna Chaki

  2. Faculty of Computer Science, Bialystok University of Technology Faculty of Computer Science, Bialystok, Poland

    Khalid Saeed

  3. DAIS—Università Ca' Foscari, Full Professor of Computer Science DAIS—Università Ca' Foscari, Mestre, Venice, Venezia, Italy

    Agostino Cortesi

  4. Computer Science & Engineering, University of Calcutta Computer Science & Engineering, Kolkata, West Bengal, India

    Nabendu Chaki

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this chapter

Cite this chapter

Nanda, A., Sa, P.K. (2017). Single-Shot Person Re-identification by Spectral Matching of Symmetry-Driven Local Features . In: Chaki, R., Saeed, K., Cortesi, A., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 567. Springer, Singapore. https://doi.org/10.1007/978-981-10-3409-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3409-1_10

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3408-4

  • Online ISBN: 978-981-10-3409-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation