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Attribute Discovery for Person Re-Identification

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MultiMedia Modeling (MMM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9517))

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Abstract

An incremental attribute discovery method for person re-identification is proposed in this paper. Recent studies have shown the effectiveness of the attribute-based approach. Unfortunately, the approach has difficulty in discriminating people who are similar in terms of the pre-defined semantic attributes. To solve this problem, we automatically discover and learn new attributes that permit successful discrimination through a pair-wise learning process. We evaluate our method on two benchmark datasets and demonstrate that it significantly improves the performance of the person re-identification task.

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References

  1. Prosser, B., Zheng, W.S., Gong, S., Xiang, T., Mary, Q.: Person re-identification by support vector ranking. In: BMVC, vol. 2, p. 6 (2010)

    Google Scholar 

  2. 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)

    Chapter  Google Scholar 

  3. Hospedales, T.M., Layne, R., Gong, S.: Attributes-based re-identification. In: Person Re-Identification (2013)

    Google Scholar 

  4. Nguyen, N.-B., Nguyen, V.-H., Duc, T.N., Le, D.-D., Duong, D.A.: AttRel: an approach to person re-identification by exploiting attribute relationships. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015, Part II. LNCS, vol. 8936, pp. 50–60. Springer, Heidelberg (2015)

    Google Scholar 

  5. Layne, R., Hospedales, T.M., Gong, S., Mary, Q.: Person re-identification by attributes. In: BMVC (2012)

    Google Scholar 

  6. Das, A., Panda, R., Roy-Chowdhury, A.: Active image pair selection for continuous person re-identification. In: ICIP (2015)

    Google Scholar 

  7. 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)

    Chapter  Google Scholar 

  8. Cancela, B., Hospedales, T.M., Gong, S.: Open-world person re-identification by multi-label assignment inference. In: BMVC (2014)

    Google Scholar 

  9. Lampert, C.H., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: CVPR, pp. 951–958 (2009)

    Google Scholar 

  10. Farhadi, A., Endres, I., Hoiem, D., Forsyth, D.: Describing objects by their attributes. In: CVPR, pp. 1778–1785 (2009)

    Google Scholar 

  11. Patterson, G., Hays, J.: Sun attribute database: discovering, annotating, and recognizing scene attributes. In: CVPR, pp. 2751–2758 (2012)

    Google Scholar 

  12. Bergamo, A., Torresani, L., Fitzgibbon, A.W.: Picodes: learning a compact code for novel-category recognition. In: NIPS, pp. 2088–2096 (2011)

    Google Scholar 

  13. Rastegari, M., Farhadi, A., Forsyth, D.: Attribute discovery via predictable discriminative binary codes. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part VI. LNCS, vol. 7577, pp. 876–889. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  14. Parikh, D.: Grauman, K.: Interactively building a discriminiative vocabulary of nameable attributes. In: CVPR, pp. 1681–1688 (2011)

    Google Scholar 

  15. Berg, T.L., Berg, A.C., Shih, J.: Automatic attribute discovery and characterization from noisy Web data. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 663–676. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Yu, F.X., Cao, L, Feris, R.S., Smith, J.R., Chang, S.F.: Designing category-level attributes for discriminative visual recognition. In: CVPR, pp. 771–778 (2013)

    Google Scholar 

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Correspondence to Takayuki Umeda .

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Umeda, T., Sun, Y., Irie, G., Sudo, K., Kinebuchi, T. (2016). Attribute Discovery for Person Re-Identification. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9517. Springer, Cham. https://doi.org/10.1007/978-3-319-27674-8_24

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  • DOI: https://doi.org/10.1007/978-3-319-27674-8_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27673-1

  • Online ISBN: 978-3-319-27674-8

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