References
Jin X, Zhu S Y, Xiao C E, et al. 3D textured model encryption via 3D Lu chaotic mapping. Sci China Inf Sci, 2017, 60: 122107
Guo L H, Guo C G, Li L, et al. Two-stage local constrained sparse coding for fine-grained visual categorization. Sci China Inf Sci, 2018, 61: 018104
Zhu J Q, Zeng H Q, Liao S C, et al. Deep hybrid similarity learning for person re-identification. IEEE Trans Circ Syst Video Technol, 2018, 28: 3183–3193
Chen Y C, Zheng W S, Lai J H, et al. An asymmetric distance model for cross-view feature mapping in person re-identification. IEEE Trans Circ Syst Video Technol, 2017, 27: 1661–1675
Liao S C, Hu Y, Zhu X Y, et al. Person reidentification by local maximal occurrence representation and metric learning. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Boston, 2015. 2197–2206
Zhu J Q, Zeng H Q, Du Y Z, et al. Person re-identification based on novel triplet convolutional neural network. J Electron Inf Technol, 2018, 40: 1012–1016
Zhu J Q, Zeng H Q, Lei Z, et al. A shortly and densely connected convolutional neural network for vehicle reidentification. In: Proceedings of International Conference on Pattern Recognition, Beijing, 2018
Zheng L, Wang S J, Zhou W G, et al. Bayes merging of multiple vocabularies for scalable image retrieval. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Columbus, 2014. 1963–1970
Liu X C, Liu W, Mei T, et al. PROVID: progressive and multimodal vehicle reidentification for large-scale urban surveillance. IEEE Trans Multimedia, 2018, 20: 645–658
Acknowledgements
This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61602191, 61871434, 61802136, 61672521), in part by Natural Science Foundation of Fujian Province (Grant Nos. 2018J01090, 2016J01308), in part by Promotion Program for Young and Middle-aged Teacher in Science and Technology Research of Huaqiao University (Grant Nos. ZQNPY418, ZQN-YX403), and in part by Scientific Research Funds of Huaqiao University (Grant No. 16BS108).
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Zhu, J., Zeng, H., Jin, X. et al. Joint horizontal and vertical deep learning feature for vehicle re-identification. Sci. China Inf. Sci. 62, 199101 (2019). https://doi.org/10.1007/s11432-018-9639-7
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DOI: https://doi.org/10.1007/s11432-018-9639-7