Abstract
Until now, most existing researches on person re-identification aim at improving the recognition rate on single dataset setting. The training data and testing data of these methods are form the same source. Although they have obtained high recognition rate in experiments, they usually perform poorly in practical applications. In this paper, we focus on the cross dataset person re-identification which make more sense in the real world. We present a deep learning framework based on convolutional neural networks to learn the person representation instead of existing hand-crafted features, and cosine metric is used to calculate the similarity. Three different datasets Shinpuhkan2014dataset, CUHK and CASPR are chosen as the training sets, we evaluate the performances of the learned person representations on VIPeR. For the training set Shinpuhkan2014dataset, we also evaluate the performances on PRID and iLIDS. Experiments show that our method outperforms the existing cross dataset methods significantly and even approaches the performances of some methods in single dataset setting.
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References
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: DeepFace: closing the gap to human-level performance in face verification. In: Conference on Computer Vision and Pattern Recognition (CVPR)
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS, pp. 1106–1114 (2012)
Kawanishi, Y., Wu, Y., Mukunoki, M., Minoh, M.: Shinpuhkan 2014: A multi-camera pedestrian dataset for tracking people across multiple cameras. In: Proceedings of the 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV) (2014)
Li, W., Zhao, R., Wang, X.: Human reidentification with transferred metric learning. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds.) ACCV 2012, Part I. LNCS, vol. 7724, pp. 31–44. Springer, Heidelberg (2013)
Li, W., Wang, X.: Locally aligned feature transforms across views. In: CVPR, pp. 3594–3601 (2013)
Weinberger, K., Blitzer, J., Saul, L.: Distance metric learning for large margin nearest neighbor classification. Adv. Neural Inf. Process. Syst. 18, 1473 (2006)
Dikmen, M., Akbas, E., Huang, T.S., Ahuja, N.: Pedestrian recognition with a learned metric. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part IV. LNCS, vol. 6495, pp. 501–512. Springer, Heidelberg (2011)
Davis, J.V., Kulis, B., Jain, P., Sra, S., Dhillon, I.S.: Information-theoretic metric learning. In: Proceedings of the 24th International Conference on Machine Learning, pp. 209–216, ACM (2007)
Zheng, W.S., Gong, S., Xiang, T.: Person re-identification by probabilistic relative distance comparison. In: CVPR, pp. 649–656 (2011)
Kostinger, M., Hirzer, M., Wohlhart, P., Roth, P.M., Bischof, H.: Large scale metric learning from equivalence constraints. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2288–2295. IEEE (2012)
Li, Z., Chang, S., Liang, F., Huang, T.S., Cao, L., Smith, J.R.: Learning locally-adaptive decision functions for person verification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3610–3617. IEEE (2013)
Guillaumin, M., Verbeek, J., Schmid, C.: Is that you? metric learning approaches for face identification. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 498–505. IEEE (2009)
Gong, S., Cristani, M., Yan, S., Loy, C.C.: Person Re-identification. Springer, London (2014)
Hu, Y., Liao, S., Lei, Z., Yi, D., Li, S.Z.: Exploring structural information and fusing multiple features for person re-identification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). pp. 794–799, IEEE (2013)
Gheissari, N., Sebastian, T.B., Hartley, R.: Person reidentification using spatiotemporal appearance. In: CVPR, vol. 2, pp. 1528–1535 (2006)
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: ICDSC, pp. 1–6 (2008)
Wang, X., Doretto, G., Sebastian, T., Rittscher, J., Tu, P.H.: Shape and appearance context modeling. In: ICCV, pp. 1–8 (2007)
Farenzena, M., Bazzani, L., Perina, A., Murino, V., Cristani, M.: Person re-identification by symmetry-driven accumulation of local features. In: CVPR, pp. 2360–2367 (2010)
Ma, B., Su, Y., Jurie, F.: Local descriptors encoded by fisher vectors for person re-identification. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 413–422. Springer, Heidelberg (2012)
Cheng, D.S., Cristani, M., Stoppa, M., Bazzani, L., Murino, V.: Custom pictorial structures for re-identification. In: BMVC, vol. 2, p. 6 (2011)
Zhao, R., Ouyang, W., Wang, X.: Unsupervised salience learning for person re-identification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3586–3593. IEEE (2013)
Zhao, R., Ouyang, W., Wang, X.: Person re-identification by salience matching. In: ICCV (2013)
Liu, Y., Shao, Y., Sun, F.: Person re-identification based on visual saliency. In: 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 884–889. IEEE (2012)
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)
Prosser, B., Zheng, W.S., Gong, S., Xiang, T., Mary, Q.: Person re-identification by support vector ranking. In: BMVC, vol. 1, p. 5 (2010)
Li, W., Wang, X.: Locally aligned feature transforms across views. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3594–3601. IEEE (2013)
Liu, C., Loy, C.C., Gong, S., Wang, G.: Pop: person re-identification post-rank optimisation. In: International Conference on Computer Vision (2013)
Ma, A., Yuen, P., Li, J.: Domain transfer support vector ranking for person re-identification without target camera label information. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 3567–3574 (2013)
Yi, D., Lei, Z., Liao, S., Li, S.Z.: Deep metric learning for person re-identification. In: International Conference on Pattern Recognition (2014)
Lecun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. In: Proceedings of the IEEE, pp. 2278–2324 (1998)
Nair, V., Hinton, G.E.: Rectified linear units improve restricted boltzmann machines. In: ICML, pp. 807–814 (2010)
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, Citeseer (2007)
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)
Ma, B., Su, Y., Jurie, F., et al.: Bicov: a novel image representation for person re-identification and face verification. In: British Machive Vision Conference (2012)
Globerson, A., Roweis, S.T.: Metric learning by collapsing classes. In: NIPS (2005)
Xing, E.P., Ng, A.Y., Jordan, M.I., Russell, S.J.: Distance metric learning with application to clustering with side-information. In: NIPS, pp. 505–512 (2002)
Acknowledgment
This work was supported by the Chinese National Natural Science Foundation Projects #61105023, #61103156, #61105037, #61203267, #61375037, National Science and Technology Support Program Project #2013BAK02B01, Chinese Academy of Sciences Project No. KGZD-EW-102-2, and AuthenMetric R&D Funds.
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Hu, Y., Yi, D., Liao, S., Lei, Z., Li, S.Z. (2015). Cross Dataset Person Re-identification. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9010. Springer, Cham. https://doi.org/10.1007/978-3-319-16634-6_47
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DOI: https://doi.org/10.1007/978-3-319-16634-6_47
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