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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 842))

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Abstract

Person re-identification (person re-ID) is refers to pedestrians matching under a multi camera network in a non-overlapping field of view, that is, whether the pedestrian targets taken by different cameras are the same. In this paper, the image based traditional person re-ID is introduced from feature description and metric learning. In addition, with the extensive application of the deep learning algorithm in recent years, it also brings about the change of person re-ID algorithm. From the three aspects of loss function design, local feature and data augmentation, this paper introduces some work of person re-ID algorithm based on deep learning. Finally, it summarizes the development of pedestrian datasets in recent years, and looks forward to the future development trend of person re-ID.

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Acknowledgments

This work was supported by the Scientific Research Fund of Hunan Provincial Education Department of China (Project No. 17A007); and the Teaching Reform and Research Project of Hunan Province of China (Project No. JG1615).

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Correspondence to Shuren Zhou .

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Zhou, S., Ke, M., Luo, P. (2019). An Overview of Image-Based Person Re-identification. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Security and Intelligence ATCI 2018. ATCI 2018. Advances in Intelligent Systems and Computing, vol 842. Springer, Cham. https://doi.org/10.1007/978-3-319-98776-7_39

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