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2017 | OriginalPaper | Chapter

A Study on Deep Convolutional Neural Network Based Approaches for Person Re-identification

Authors : Harendra Chahar, Neeta Nain

Published in: Pattern Recognition and Machine Intelligence

Publisher: Springer International Publishing

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Abstract

Person re-identification is a process to identify the same person again viewed by disjoint field of view of cameras. It is a challenging problem due to visual ambiguity in a person’s appearance across different camera views. These difficulties are often compounded by low resolution surveillance images, occlusion, background clutter and varying lighting conditions. In recent years, person re-identification community obtained large size of annotated datasets and deep learning architecture based approaches have obtained significant improvement in the accuracy over the years as compared to hand-crafted approaches. In this survey paper, we have classified deep learning based approaches into two categories, i.e., image-based and video-based person re-identification. We have also presented the currently ongoing under developing works, issues and future directions for person re-identification.

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Metadata
Title
A Study on Deep Convolutional Neural Network Based Approaches for Person Re-identification
Authors
Harendra Chahar
Neeta Nain
Copyright Year
2017
Book
Pattern Recognition and Machine Intelligence

Print ISBN: 978-3-319-69899-1

Electronic ISBN: 978-3-319-69900-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-69900-4_69

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