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Global Descriptors of Convolution Neural Networks for Remote Scene Images Classification Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Pedestrian Retrieval Using Valuable Absence Augmentation

Authors : Xiaolong Hao, Shuang Liu, Zhong Zhang, Tariq S. Durrani

Published in: Artificial Intelligence in China

Publisher: Springer Singapore

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Abstract

In this paper, we propose a novel data augmentation method named valuable absence augmentation (VAA) in order to alleviate the overfitting and evaluate the influence of the pedestrian valuable parts for the network performance. Specifically, we first train a base convolutional neural network model and obtain the attention map of the pedestrian. Then, we use the attention map to generate new samples. Finally, original samples and new samples are combined to fine-tune the base network model. We conduct experiments on a large-scale pedestrian retrieval database, i.e., Market-1501. Experimental results show that the pedestrian valuable part has a crucial influence for the network performance and that the proposed method achieves better performance than other state-of-the-art methods.

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Literature
1.
Liao S, Hu Y, Zhu X, Li S (2015) Person re-identification by local maximal occurrence representation and metric learning. In: IEEE conference on computer vision and pattern recognition, pp 2197–2206
2.
Liu S, Hao X, Zhang Z (2018) Pedestrian retrieval via part-based gradation regularization in sensor networks. IEEE Access 6:38171–38178CrossRef
3.
Zhang Z, Wang C, Xiao B, Zhou W, Liu S, Shi C (2013) Cross-view action recognition via a continuous virtual path. In: IEEE conference on computer vision and pattern recognition, pp 2690–2697
4.
Zhang Z, Wang C, Xiao B, Zhou W, Liu S (2014) Cross-view action recognition using contextual maximum margin clustering. IEEE Trans Circ Syst Video Technol 24(10):1663–1668CrossRef
5.
Li A, Wu Z, Lu H, Chen D, Sun G (2018) Collaborative self-regression method with nonlinear feature based on multi-task learning for image classification. IEEE Access 6:43513–43525CrossRef
6.
Li A, Chen D, Wu Z, Sun G, Lin K (2018) Self-supervised sparse coding scheme for image classification based on low rank representation. PLOS One 13(6):1–15
7.
Xiao T, Li H, Ouyang W, Wang X (2016) Learning deep feature representations with domain guided dropout for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 1249–1258
8.
Zheng Z, Zheng L, Yang Y (2017) A discriminatively learned CNN embedding for person re-identification. ACM Trans Multimedia Comput Commun Appl 14(1):1–20MathSciNetCrossRef
9.
Sun Y, Zheng L, Yang Y, Tian Q, Wang S (2018) Beyond part models: person retrieval with refined part pooling (and a strong convolutional baseline). In: European conference on computer vision, pp 1–17CrossRef
10.
Zhong Z, Zheng L, Li S, Yang Y (2018) Generalizing a person retrieval model hetero-and homogeneously. In: European conference on computer vision, pp 172–188CrossRef
11.
Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097–1105
12.
Simonyan K, Zisserman A (2015) Very deep convolutional networks for large-scale image recognition. In: International conference on learning representations, pp 135–153
13.
14.
He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: IEEE conference on computer vision and pattern recognition, pp 770–778
15.
Zheng L, Shen L, Tian L, Wang S, Wang J, Tian Q (2015) Scalable person re-identification: a benchmark. In: IEEE international conference on computer vision, pp 1116–1124
16.
Felzenszwalb PF, Girshick RB, Mcallester DA, Ramanan D (2010) Object detection with discriminatively trained part-based models. IEEE Trans Pattern Anal Mach Intell 32:1627–1645CrossRef
17.
Su C, Zhang S, Xing J, Gao W, Tian Q (2016) Deep attributes driven multi-camera person re-identification. In: European conference on computer vision, pp 475–491CrossRef
18.
Varior RR, Haloi M, Wang G (2016) Gated siamese convolutional neural network architecture for human re-identification. In: European conference on computer vision, pp 791–808CrossRef
19.
20.
Zhao L, Li X, Wang J, Zhuang Y (2017) Deeply-learned part-aligned representations for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 3219–3228
21.
Sun Y, Zheng L, Deng W, Wang S (2017) SVDNet for pedestrian retrieval. In: IEEE international conference on computer vision, pp 3820–3828
22.
Zheng Z, Zheng L, Yang Y (2017) Unlabeled samples generated by GAN improve the person re-identification baseline in vitro. In: IEEE international conference on computer vision, pp 3754–3762
23.
Lin Y, Zheng L, Zheng Z, Wu Y, Yang Y (2017) Improving person re-identification by attribute and identity learning (Online). arXiv:​1703.​07220
24.
Metadata
Title
Pedestrian Retrieval Using Valuable Absence Augmentation
Authors
Xiaolong Hao
Shuang Liu
Zhong Zhang
Tariq S. Durrani
Copyright Year
2020
Publisher
Springer Singapore
Book
Artificial Intelligence in China

Print ISBN: 978-981-15-0186-9

Electronic ISBN: 978-981-15-0187-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-0187-6_29