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2018 | OriginalPaper | Chapter

Vehicle Verification Based on Deep Siamese Network with Similarity Metric

Authors : Qian Zhang, Mingtao Pei, Mei Chen, Yunde Jia

Published in: Advances in Multimedia Information Processing – PCM 2017

Publisher: Springer International Publishing

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Abstract

Vehicle verification is a challenging research problem with important practical applications. Most prior work focused on either feature learning or distance metric learning, which could not guarantee the compatibility of the learned feature and the distance metric. In this paper, we propose an end-to-end model based on the Siamese Convolutional Neural Network (CNN), which integrates distance metric learning and feature learning into a unified framework. The network is trained by contrastive loss and a similarity metric loss defined by joint Bayesian to learn more discriminative features for vehicle verification. The experimental results demonstrate the effectiveness of the proposed method.

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Literature
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), pp. 3908–3916 (2015)
2.
3.
Chen, D., Cao, X., Wen, F., Sun, J.: Blessing of dimensionality: high-dimensional feature and its efficient compression for face verification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3025–3032 (2013)
4.
Chen, J.C., Patel, V.M., Chellappa, R.: Unconstrained face verification using deep CNN features. In: IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1–9. IEEE (2016)
5.
Chopra, S., Hadsell, R., LeCun, Y.: Learning a similarity metric discriminatively, with application to face verification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. 539–546. IEEE (2005)
6.
Ding, S., Lin, L., Wang, G., Chao, H.: Deep feature learning with relative distance comparison for person re-identification. Pattern Recogn. 48(10), 2993–3003 (2015)CrossRef
7.
Hadsell, R., Chopra, S., LeCun, Y.: Dimensionality reduction by learning an invariant mapping. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 1735–1742. IEEE (2006)
8.
Hu, J., Lu, J., Tan, Y.P.: Discriminative deep metric learning for face verification in the wild. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1875–1882 (2014)
9.
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., Darrell, T.: Caffe: convolutional architecture for fast feature embedding. In: the 22nd ACM International Conference on Multimedia (ACM MM), pp. 675–678. ACM (2014)
10.
Kwong, K., Kavaler, R., Rajagopal, R., Varaiya, P.: Arterial travel time estimation based on vehicle re-identification using wireless magnetic sensors. Transp. Res. Part C: Emerg. Technol. 17(6), 586–606 (2009)CrossRef
11.
Li, Z., Chang, S., Liang, F., Huang, T.S., Cao, L., Smith, J.R.: Learning locally-adaptive decision functions for person verification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3610–3617 (2013)
12.
Liang, M., Huang, X., Chen, C.H., Chen, X., Tokuta, A.: Counting and classification of highway vehicles by regression analysis. IEEE Trans. Intell. Transp. Syst. (TITS) 16(5), 2878–2888 (2015)CrossRef
13.
Liu, H., Tian, Y., Yang, Y., Pang, L., Huang, T.: Deep relative distance learning: tell the difference between similar vehicles. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2167–2175 (2016)
14.
Lu, C., Tang, X.: Surpassing human-level face verification performance on LFW with GaussianFace. In: Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI) (2015)
15.
16.
Mignon, A., Jurie, F.: PCCA: a new approach for distance learning from sparse pairwise constraints. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2666–2672. IEEE (2012)
17.
Prince, S., Li, P., Fu, Y., Mohammed, U., Elder, J.: Probabilistic models for inference about identity. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 34(1), 144–157 (2012)CrossRef
18.
Rao, Y.: Automatic vehicle recognition in multiple cameras for video surveillance. Vis. Comput. 31(3), 271–280 (2015)CrossRef
19.
Sun, Y., Wang, X., Tang, X.: Hybrid deep learning for face verification. In: IEEE International Conference on Computer Vision (ICCV), pp. 1489–1496 (2013)
20.
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: Deepface: closing the gap to human-level performance in face verification. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1701–1708 (2014)
21.
Wang, T., Zhu, Z., Hammoud, R.: Audio-visual feature fusion for vehicles classification in a surveillance system. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 381–386 (2013)
22.
Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res. 10(Feb), 207–244 (2009)
23.
Xiang, S., Nie, F., Zhang, C.: Learning a Mahalanobis distance metric for data clustering and classification. Pattern Recogn. 41(12), 3600–3612 (2008)CrossRef
24.
Zhang, Z., Chen, Y., Saligrama, V.: A novel visual word co-occurrence model for person re-identification. arXiv preprint arXiv:​1410.​6532 (2014)
25.
Zheng, W.S., Gong, S., Xiang, T.: Person re-identification by probabilistic relative distance comparison. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 649–656. IEEE (2011)
Metadata
Title
Vehicle Verification Based on Deep Siamese Network with Similarity Metric
Authors
Qian Zhang
Mingtao Pei
Mei Chen
Yunde Jia
Copyright Year
2018
Book
Advances in Multimedia Information Processing – PCM 2017

Print ISBN: 978-3-319-77379-7

Electronic ISBN: 978-3-319-77380-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-77380-3_74