Gated siamese convolutional neural network architecture for human re-identification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9912 LNCS, Issue , 2016, Pages 791-808

  Varior, Rahul Rama ^a   Haloi, Mrinal ^a   Wang, Gang ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Deep Convolutional Neural Networks; Gating function; Human re identification; Matching gate; Siamese Convolutional Neural Network

Indexed keywords

CONVOLUTION; DEEP NEURAL NETWORKS; IMAGE PROCESSING; NETWORK ARCHITECTURE; SECURITY SYSTEMS;

GATING FUNCTIONS; LOCAL PATTERNS; MATCHING GATE; MID-LEVEL FEATURES; MULTIPLE CAMERAS; RE IDENTIFICATIONS; RESEARCH PROBLEMS; VISUAL SURVEILLANCE;

CONVOLUTIONAL NEURAL NETWORKS;

EID: 84990058340     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46484-8_48     Document Type: Conference Paper

References (57)

1. Ahmed, E., Jones, M., Marks, T.K.: An improved deep learning architecture for person re-identification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
2. Bromley, J., Guyon, I., LeCun, Y., Säckinger, E., Shah, R.: Signature verification using a “siamese” time delay neural network. In: Advances in Neural Information Processing Systems, vol. 6 (1994)
3. Chen, D., Yuan, Z., Chen, B., Zheng, N.: Similarity learning with spatial constraints for person re-identification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
4. Cheng, D., Gong, Y., Zhou, S., Wang, J., Zheng, N.: Person re-identification by multi-channel parts-based CNN with improved triplet loss function. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
5. Cheng, D.S., Cristani, M., Stoppa, M., Bazzani, L., Murino, V.: Custom pictorial structures for re-identification. In: Proceedings of the British Machine Vision Conference (BMVC) (2011)
6. Dauphin, Y.N., de Vries, H., Chung, J., Bengio, Y.: RMSProp and equilibrated adaptive learning rates for non-convex optimization. CoRR abs/1502.04390 (2015). http://arxiv.org/abs/1502.04390
7. Davis, J.V., Kulis, B., Jain, P., Sra, S., Dhillon, I.S.: Information-theoretic metric learning. In: Proceedings of the International Conference on Machine Learning (ICML) (2007)
8. Farenzena, M., Bazzani, L., Perina, A., Murino, V., Cristani, M.: Person reidentification by symmetry-driven accumulation of local features. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2010)
9. Gers, F., Schmidhuber, J., Cummins, F.: Learning to forget: continual prediction with LSTM. In: International Conference on Artificial Neural Networks, ICANN 1999 (1999)
10. 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 (PETS) (2007)
11. Guillaumin, M., Verbeek, J., Schmid, C.: Is that you? Metric learning approaches for face identification. In: IEEE 12th International Conference on Computer Vision, ICCV 2009 (2009)
12. Hadsell, R., Chopra, S., LeCun, Y.: Dimensionality reduction by learning an invariant mapping. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2006 (2006)
13. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR abs/1512.03385 (2015). http://arxiv.org/abs/1512.03385
14. He, K., Zhang, X., Ren, S., Sun, J.: Delving deep into rectifiers: surpassing humanlevel performance on imagenet classification. CoRR abs/1502.01852 (2015). http://arxiv.org/abs/1502.01852
15. Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9, 1735-1780 (1997)
16. Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. CoRR abs/1502.03167 (2015). http://arxiv.org/abs/1502.03167
17. Karpathy, A., Johnson, J., Li, F.: Visualizing and understanding recurrent networks. CoRR abs/1506.02078 (2015). http://arxiv.org/abs/1506.02078
18. Kostinger, M., Hirzer, M., Wohlhart, P., Roth, P., Bischof, H.: Large scale metric learning from equivalence constraints. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2012)
19. Kviatkovsky, I., Adam, A., Rivlin, E.: Color invariants for person reidentification. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 35, 1622-1634 (2013)
20. 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). doi:10.1007/ 978-3-642-37331-2_3
21. Li, W., Zhao, R., Xiao, T., Wang, X.: DeepReID: deep filter pairing neural network for person re-identification. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 152-159, June 2014
22. Li, Z., Chang, S., Liang, F., Huang, T.S., Cao, L., Smith, J.R.: Learning locallyadaptive decision functions for person verification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2013)
23. Liao, S., Hu, Y., Zhu, X., Li, S.Z.: Person re-identification by local maximal occurrence representation and metric learning. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
24. Liao, S., Li, S.Z.: Efficient PSD constrained asymmetric metric learning for person re-identification. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3685-3693 (2015)
25. Liao, S., Zhao, G., Kellokumpu, V., Pietikainen, M., Li, S.: Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2010)
26. Liu, J., Shahroudy, A., Xu, D., Wang, G.: Spatio-temporal LSTM with trust gates for 3D human action recognition. In: European Conference on Computer Vision (ECCV) (2016)
27. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. (IJCV) 60, 91-110 (2004)
28. Ma, B., Su, Y., Jurie, F.: BiCov: a novel image representation for person reidentification and face verification. In: Proceedings of the British Machive Vision Conference (BMVC) (2012)
29. Matsukawa, T., Okabe, T., Suzuki, E., Sato, Y.: Hierarchical Gaussian descriptor for person re-identification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
30. Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 24, 971-987 (2002)
31. Pedagadi, S., Orwell, J., Velastin, S., Boghossian, B.: Local fisher discriminant analysis for pedestrian re-identification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2013)
32. Rama Varior, R., Wang, G.: Hierarchical invariant feature learning with marginalization for person re-identification. ArXiv e-prints (2015)
33. Shen, Y., Lin, W., Yan, J., Xu, M., Wu, J., Wang, J.: Person re-identification with correspondence structure learning. In: The IEEE International Conference on Computer Vision (ICCV) (2015)
34. Shi, Z., Hospedales, T.M., Xiang, T.: Transferring a semantic representation for person re-identification and search. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
35. Shuai, B., Wang, G., Zuo, Z., Wang, B., Zhao, L.: Integrating parametric and non-parametric models for scene labeling. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4249-4258, June 2015
36. Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR abs/1409.1556 (2014). http://arxiv.org/abs/1409.1556
37. Srivastava, R.K., Greff, K., Schmidhuber, J.:Training very deep networks. In: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 28, pp. 2377-2385. Curran Associates, Inc. (2015). http://papers.nips.cc/paper/5850-training-very-deep-networks.pdf
38. Su, C., Yang, F., Zhang, S., Tian, Q., Davis, L.S., Gao, W.: Multi-task learning with low rank attribute embedding for person re-identification. In: The IEEE International Conference on Computer Vision (ICCV), December 2015
39. Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. CoRR abs/1512.00567 (2015). http://arxiv.org/abs/1512.00567
40. Varior, R.R., Shuai, B., Lu, J., Xu, D., Wang, G.: A siamese long short-term memory architecture for human re-identification. In: European Conference on Computer Vision (ECCV) (2016)
41. Varior, R.R., Wang, G., Lu, J., Liu, T.: Learning invariant color features for person re-identification. IEEE Trans. Image Process. PP(99), 1 (2016)
42. Vedaldi, A., Lenc, K.: Matconvnet-convolutional neural networks for matlab (2015)
43. Wang, F., Zuo, W., Lin, L., Zhang, D., Zhang, L.: Joint learning of single-image and cross-image representations for person re-identification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
44. Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res. (JMLR) 10, 207-244 (2009)
45. Xiao, T., Li, H., Ouyang, W., Wang, X.: Learning deep feature representations with domain guided dropout for person re-identification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
46. Xiong, F., Gou, M., Camps, O., Sznaier, M.: Person re-identification using kernelbased metric learning methods. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014, Part VII. LNCS, vol. 8695, pp. 1-16. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10584-0_1
47. Yang, Y., Liao, S., Lei, Z., Yi, D., Li, S.Z.: Color models and weighted covariance estimation for person re-identification. In: Proceedings of International Conference on Pattern Recognition (ICPR) (2014)
48. Yang, Y., Yang, J., Yan, J., Liao, S., Yi, D., Li, S.Z.: Salient color names for person re-identification. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014, Part I. LNCS, vol. 8689, pp. 536-551. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10590-1_35
49. Yi, D., Lei, Z., Liao, S., Li, S.Z.: Deep metric learning for person re-identification. In: Proceedings of International Conference on Pattern Recognition (ICPR) (2014)
50. Zhang, L., Xiang, T., Gong, S.: Learning a discriminative null space for person reidentification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
51. Zhang, Y., Li, B., Lu, H., Irie, A., Ruan, X.: Sample-specific SVM learning for person re-identification. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
52. Zhang, Z., Chen, Y., Saligrama, V.: A novel visual word co-occurrence model for person re-identification. In: European Conference on Computer Vision Workshop on Visual Surveillance and Re-identification (ECCV Workshop) (2014)
53. Zhao, R., Ouyang, W., Wang, X.: Person re-identification by salience matching. In: IEEE International Conference on Computer Vision (ICCV) (2013)
54. Zhao, R., Ouyang, W., Wang, X.: Unsupervised salience learning for person reidentification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2013)
55. Zhao, R., Ouyang, W., Wang, X.: Learning mid-level filters for person reidentfiation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014)
56. Zheng, L., Wang, S., Tian, L., He, F., Liu, Z., Tian, Q.: Query-adaptive late fusion for image search and person re-identification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
57. Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., Bu, J., Tian, Q.: Scalable person re-identification: a benchmark. In: IEEE International Conference on Computer Vision (2015)