Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Improving a Switched Vector Field Model for Pedestrian Motion Analysis Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Person Re-Identification with a Body Orientation-Specific Convolutional Neural Network

Authors : Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla Baskurt

Published in: Advanced Concepts for Intelligent Vision Systems

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Person re-identification consists in matching images of a particular person captured in a network of cameras with non-overlapping fields of view. The challenges in this task arise from the large variations of human appearance. In particular, the same person could show very different appearances from different points of view. To address this challenge, in this paper we propose an Orientation-Specific Convolutional Neural Network (OSCNN) framework which jointly performs body orientation regression and extracts orientation-specific deep representations for person re-identification. A robust joint embedding is obtained by combining feature representations under different body orientations. We experimentally show on two public benchmarks that taking into account body orientations improves the person re-identification performance. Moreover, our approach outperforms most of the previous state-of-the-art re-identification methods on these benchmarks.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Matrix Descriptor of Changes (MDC): Activity Recognition Based on Skeleton
next chapter Distributed Estimation of Vector Fields
Literature
1.
Ahmed, E., Jones, M., Marks, T.K.: An improved deep learning architecture for person re-identification. In: CVPR, pp. 3908–3916 (2015)
2.
Bak, S., Zaidenberg, S., Boulay, B., Bremond, F.: Improving person re-identification by viewpoint cues. In: IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 175–180. IEEE (2014)
3.
Chen, W., Chen, X., Zhang, J., Huang, K.: A multi-task deep network for person re-identification. In: AAAI, pp. 3988–3994 (2017)
4.
Cheng, D., Gong, Y., Zhou, S., Wang, J., Zheng, N.: Person re-identification by multi-channel parts-based cnn with improved triplet loss function. In: CVPR, pp. 1335–1344 (2016)
5.
García, J., Martinel, N., Foresti, G.L., Gardel, A., Micheloni, C.: Person orientation and feature distances boost re-identification. In: International Conference on Pattern Recognition (ICPR), pp. 4618–4623. IEEE (2014)
6.
Gray, D., Tao, H.: Viewpoint invariant pedestrian recognition with an ensemble of localized features. In: ECCV, pp. 262–275 (2008)
7.
Koestinger, M., Hirzer, M., Wohlhart, P., Roth, P.M., Bischof, H.: Large scale metric learning from equivalence constraints. In: CVPR, pp. 2288–2295 (2012)
8.
Li, D., Chen, X., Zhang, Z., Huang, K.: Learning deep context-aware features over body and latent parts for person re-identification. In: CVPR, pp. 384–393 (2017)
9.
Li, W., Wang, X.: Locally aligned feature transforms across views. In: CVPR, pp. 3594–3601 (2013)
10.
Li, W., Zhao, R., Wang, X.: Human reidentification with transferred metric learning. In: ACCV (2012)
11.
Li, W., Zhao, R., Xiao, T., Wang, X.: Deepreid: deep filter pairing neural network for person re-identification. In: CVPR, pp. 152–159 (2014)
12.
Li, W., Zhu, X., Gong, S.: Person re-identification by deep joint learning of multi-loss classification. In: International Joint Conference on Artificial Intelligence (2017)
13.
Liao, S., Hu, Y., Zhu, X., Li, S.Z.: Person re-identification by local maximal occurrence representation and metric learning. In: CVPR (2015)
14.
Lisanti, G., Masi, I., Del Bimbo, A.: Matching people across camera views using kernel canonical correlation analysis. In: Proceedings of the International Conference on Distributed Smart Cameras, p. 10. ACM (2014)
15.
Ma, L., Yang, X., Tao, D.: Person re-identification over camera networks using multi-task distance metric learning. IEEE Trans. Image Process. 23(8), 3656–3670 (2014)MathSciNetCrossRefMATH
16.
Ma, L., Liu, H., Hu, L., Wang, C., Sun, Q.: Orientation driven bag of appearances for person re-identification. arXiv preprint arXiv:​1605.​02464 (2016)
17.
Pedagadi, S., Orwell, J., Velastin, S., Boghossian, B.: Local fisher discriminant analysis for pedestrian re-identification. In: CVPR, pp. 3318–3325 (2013)
18.
Sarfraz, M.S., Schumann, A., Wang, Y., Stiefelhagen, R.: Deep view-sensitive pedestrian attribute inference in an end-to-end model. In: British Machine Vision Conference (BMVC) (2017)
19.
Shi, H., et al.: Embedding deep metric for person re-identification: a study against large variations. In: ECCV, pp. 732–748 (2016)
20.
Subramaniam, A., Chatterjee, M., Mittal, A.: Deep neural networks with inexact matching for person re-identification. In: NIPS, pp. 2667–2675 (2016)
21.
Sun, Y., Zheng, L., Deng, W., Wang, S.: Svdnet for pedestrian retrieval. In: International Conference on Computer Vision (2017)
22.
Varior, R.R., Haloi, M., Wang, G.: Gated siamese convolutional neural network architecture for human re-identification. In: ECCV, pp. 791–808 (2016)
23.
Verma, A., Hebbalaguppe, R., Vig, L., Kumar, S., Hassan, E.: Pedestrian detection via mixture of CNN experts and thresholded aggregated channel features. In: ICCV Workshops, pp. 163–171 (2015)
24.
Wu, L., Shen, C., Hengel, A.v.d.: Personnet: Person re-identification with deep convolutional neural networks. arXiv preprint arXiv:​1601.​07255 (2016)
25.
Yi, D., Lei, Z., Liao, S., Li, S.Z.: Deep metric learning for person re-identification. In: International Conference on Pattern Recognition, pp. 34–39 (2014)
26.
Yu, R., Zhou, Z., Bai, S., Bai, X.: Divide and fuse: a re-ranking approach for person re-identification. In: British Machine Vision Conference (BMVC) (2017)
27.
Zhao, H., et al.: Spindle net: person re-identification with human body region guided feature decomposition and fusion. In: CVPR, pp. 1077–1085 (2017)
28.
Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., Tian, Q.: Scalable person re-identification: a benchmark. In: International Conference on Computer Vision (2015)
29.
Zheng, Z., Zheng, L., Yang, Y.: Unlabeled samples generated by gan improve the person re-identification baseline in vitro. In: International Conference on Computer Vision (2017)
30.
Zhong, Z., Zheng, L., Cao, D., Li, S.: Re-ranking person re-identification with k-reciprocal encoding. In: CVPR (2017)
Metadata
Title
Person Re-Identification with a Body Orientation-Specific Convolutional Neural Network
Authors
Yiqiang Chen
Stefan Duffner
Andrei Stoian
Jean-Yves Dufour
Atilla Baskurt
Copyright Year
2018
Book
Advanced Concepts for Intelligent Vision Systems

Print ISBN: 978-3-030-01448-3

Electronic ISBN: 978-3-030-01449-0

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-01449-0_3

Premium Partner

    Image Credits