Abstract
In this article, we introduce a method to overcome one of the main challenges of person reidentification in multicamera networks, namely cross-view appearance changes. The proposed solution addresses the extreme variability of person appearance in different camera views by exploiting multiple feature representations. For each feature, kernel canonical correlation analysis with different kernels is employed to learn several projection spaces in which the appearance correlation between samples of the same person observed from different cameras is maximized. An iterative logistic regression is finally used to select and weight the contributions of each projection and perform the matching between the two views. Experimental evaluation shows that the proposed solution obtains comparable performance on the VIPeR and PRID 450s datasets and improves on the PRID and CUHK01 datasets with respect to the state of the art.
- Ejaz Ahmed, Michael Jones, and Tim K. Marks. 2015. An improved deep learning architecture for person re-identification. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Cross Ref
- Le An, Mehran Kafai, Songfan Yang, and Bir Bhanu. 2013. Reference-based person re-identification. In Proceedings of the International Conference on Advanced Video and Signal Based Surveillance.Google Scholar
Cross Ref
- Le An, Mehran Kafai, Songfan Yang, and Bir Bhanu. 2016. Person reidentification with reference descriptor. IEEE Transactions on Circuits and Systems for Video Technology 26, 4, 776--787. Google Scholar
Digital Library
- Le An, Songfan Yang, and Bir Bhanu. 2015. Person re-identification by robust canonical correlation analysis. IEEE Signal Processing Letters 22, 8, 1103--1107. Google Scholar
Cross Ref
- Apurva Bedagkar-Gala and Shishir K. Shah. 2014. A survey of approaches and trends in person re-identification. Image and Vision Computing 32, 4, 270--286. Google Scholar
Digital Library
- Dong Seon Cheng, Marco Cristani, Michele Stoppa, Loris Bazzani, and Vittorio Murino. 2011. Custom pictorial structures for re-identification. In Proceedings of the British Machine Vision Conference. Google Scholar
Cross Ref
- Navneet Dalal and Bill Triggs. 2005. Histograms of oriented gradients for human detection. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Raphael Felipe de Carvalho Prates and William Robson Schwartz. 2015. Appearance-based person re-identification by intra-camera discriminative models and rank aggregation. In Proceedings of the International Conference on Biometrics.Google Scholar
Cross Ref
- Gianfranco Doretto, Thomas Sebastian, Peter Tu, and Jens Rittscher. 2011. Appearance-based person reidentification in camera networks: Problem overview and current approaches. Journal of Ambient Intelligence and Humanized Computing 2, 2, 127--151. Google Scholar
Cross Ref
- Michela Farenzena, Loris Bazzani, Alessandro Perina, Vittorio Murino, and Marco Cristani. 2010. Person re-identification by symmetry-driven accumulation of local features. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Cross Ref
- Douglas Gray and Hai Tao. 2008. Viewpoint invariant pedestrian recognition with an ensemble of localized features. In Proceedings of the European Conference on Computer Vision. Google Scholar
Digital Library
- Matthieu Guillaumin, Jakob Verbeek, and Cordelia Schmid. 2009. Is that you? Metric learning approaches for face identification. In Proceedings of the International Conference on Computer Vision. Google Scholar
Cross Ref
- David R. Hardoon, Sandor Szedmak, and John Shawe-Taylor. 2004. Canonical correlation analysis: An overview with application to learning methods. Neural Computation 16, 12, 2639--2664. Google Scholar
Digital Library
- Martin Hirzer, Peter M. Roth, and Horst Bischof. 2012a. Person re-identification by efficient impostor-based metric learning. In Proceedings of the International Conference on Advanced Video and Signal Based Surveillance. Google Scholar
Digital Library
- Martin Hirzer, Peter M. Roth, Martin Köstinger, and Horst Bischof. 2012b. Relaxed pairwise learned metric for person re-identification. In Proceedings of the European Conference on Computer Vision. Google Scholar
Digital Library
- Svebor Karaman and Andrew D. Bagdanov. 2012. Identity inference: Generalizing person re-identification scenarios. In Proceedings of the European Conference on Computer Vision Workshops. Google Scholar
Digital Library
- Svebor Karaman, Giuseppe Lisanti, Andrew D. Bagdanov, and Alberto Del Bimbo. 2014. Leveraging local neighborhood topology for large scale person re-identification. Pattern Recognition 47, 12, 3767--3778. Google Scholar
Cross Ref
- Martin Köstinger, Martin Hirzer, Paul Wohlhart, Peter M. Roth, and Horst Bischof. 2012. Large scale metric learning from equivalence constraints. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Wei Li and Xiaogang Wang. 2013. Locally aligned feature transforms across views. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Wei Li, Rui Zhao, and Xiaogang Wang. 2013. Human reidentification with transferred metric learning. In Proceedings of the Asian Conference on Computer Vision. Google Scholar
Digital Library
- Wei Li, Rui Zhao, Tong Xiao, and Xiaogang Wang. 2014. DeepReID: Deep filter pairing neural network for person re-identification. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Shengcai Liao, Yang Hu, Xiangyu Zhu, and Stan Z. Li. 2015. Person re-identification by local maximal occurrence representation and metric learning. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Cross Ref
- Giuseppe Lisanti, Iacopo Masi, Andrew D. Bagdanov, and Alberto Del Bimbo. 2015. Person re-identification by iterative re-weighted sparse ranking. IEEE Transactions on Pattern Analysis and Machine Intelligence 37, 8, 1629--1642. Google Scholar
Digital Library
- Giuseppe Lisanti, Iacopo Masi, and Alberto Del Bimbo. 2014. Matching people across camera views using kernel canonical correlation analysis. In Proceedings of the ACM/IEEE International Conference on Distributed Smart Cameras. Google Scholar
Digital Library
- Hao Liu, Meibin Qi, and Jianguo Jiang. 2015a. Kernelized relaxed margin components analysis for person re-identification. IEEE Signal Processing Letters 22, 7, 910--914. Google Scholar
Cross Ref
- Xiaokai Liu, Hongyu Wang, Yi Wu, Jimei Yang, and Ming-Hsuan Yang. 2015b. An ensemble color model for human re-identification. In Proceedings of the Winter Conference on Applications of Computer Vision. Google Scholar
Digital Library
- T. Ojala, M. Pietikainen, and T. Maenpaa. 2002. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 7, 971--987. Google Scholar
Digital Library
- Sakrapee Paisitkriangkrai, Chunhua Shen, and Anton van den Hengel. 2015. Learning to rank in person re-identification with metric ensembles. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Cross Ref
- Bryan Prosser, Wei-Shi Zheng, Shaogang Gong, and Tao Xiang. 2010. Person re-identification by support vector ranking. In Proceedings of the British Machine Vision Conference. Google Scholar
Cross Ref
- Ali Rahimi and Benjamin Recht. 2007. Random features for large-scale kernel machines. In Proceedings of the Conference on Neural Information Processing Systems. Google Scholar
Digital Library
- Peter M. Roth, Martin Hirzer, Martin Koestinger, Csaba Beleznai, and Horst Bischof. 2014. Mahalanobis distance learning for person re-identification. In Person Re-Identification, S. Gong, M. Cristani, S. Yan, and C. C. Loy (Eds.). Springer, London, UK, 247--267. Google Scholar
Cross Ref
- Yang Shen, Weiyao Lin, Junchi Yan, Mingliang Xu, Jianxin Wu, and Jingdong Wang. 2015. Person re-identification with correspondence structure learning. In Proceedings of the International Conference on Computer Vision. Google Scholar
Digital Library
- Zhiyuan Shi, Timothy M. Hospedales, and Tao Xiang. 2015. Transferring a semantic representation for person re-identification and search. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Cross Ref
- Yaniv Taigman, Ming Yang, Marc’Aurelio Ranzato, and Lior Wolf. 2014. DeepFace: Closing the gap to human-level performance in face verification. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Roberto Vezzani, Davide Baltieri, and Rita Cucchiara. 2013. People reidentification in surveillance and forensics: A survey. ACM Computing Surveys 46, 2, 29:1--29:37. Google Scholar
Digital Library
- Jin Wang, Nong Sang, Zheng Wang, and Changxin Gao. 2016. Similarity learning with top-heavy ranking loss for person re-identification. IEEE Signal Processing Letters 23, 1, 84--88. Google Scholar
Cross Ref
- Weiran Wang and Karen Livescu. 2016. Large-scale approximate kernel canonical correlation analysis. In Proceedings of the International Conference on Learning Representations.Google Scholar
- Kilian Q. Weinberger and Lawrence K. Saul. 2009. Distance metric learning for large margin nearest neighbor classification. Journal of Machine Learning Research 10, 207--244. Google Scholar
Digital Library
- Fei Xiong, Mengran Gou, Octavia Camps, and Mario Sznaier. 2014. Person re-identification using kernel-based metric learning methods. In Proceedings of the European Conference on Computer Vision. Google Scholar
Cross Ref
- Yang Yang, Jimei Yang, Junjie Yan, Shengcai Liao, Dong Yi, and Stan Z. Li. 2014. Salient color names for person re-identification. In Proceedings of the European Conference on Computer Vision. Google Scholar
Cross Ref
- Dong Yi, Zhen Lei, and Stan Z. Li. 2014a. Deep metric learning for person re-identification. In Proceedings of the International Conference on Pattern Recognition. Google Scholar
Digital Library
- Dong Yi, Zhen Lei, and Stan Z. Li. 2014b. Deep metric learning for practical person re-identification. arXiv:1407.4979.Google Scholar
- Rui Zhao, Wanli Ouyang, and Xiaogang Wang. 2013a. Person re-identification by salience matching. In Proceedings of the International Conference on Computer Vision. Google Scholar
Digital Library
- Rui Zhao, Wanli Ouyang, and Xiaogang Wang. 2013b. Unsupervised salience learning for person re-identification. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Rui Zhao, Wanli Ouyang, and Xiaogang Wang. 2014. Learning mid-level filters for person re-identification. In Proceedings of the Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
Index Terms
Multichannel-Kernel Canonical Correlation Analysis for Cross-View Person Reidentification
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