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Video Person Re-Identification for Wide Area Tracking Based on Recurrent Neural Networks.
- Source :
-
IEEE Transactions on Circuits & Systems for Video Technology . Sep2019, Vol. 29 Issue 9, p2613-2626. 14p. - Publication Year :
- 2019
-
Abstract
- In this paper, we propose a video-based person re-identification system for wide area tracking based on a recurrent neural network architecture. Given short video sequences of a person, generated by a tracking algorithm, our video re-identification algorithm links these tracklets in full trajectories across a network of non-overlapping cameras in an open-world scenario. In our system, features are first extracted from each frame using a convolutional neural network. Then, a recurrent layer combines information across time-steps. The features from all time-steps are finally combined using temporal pooling to give an overall appearance feature for the complete sequence. Our system is trained to perform re-identification using a Siamese network architecture. Experiments are conducted on the iLIDS-VID and PRID-2011 video re-identification data sets as well as in the DukeMTMC multi-camera tracking data set. [ABSTRACT FROM AUTHOR]
- Subjects :
- *RECURRENT neural networks
*TRACKING algorithms
*IMAGE color analysis
*VIDEOS
Subjects
Details
- Language :
- English
- ISSN :
- 10518215
- Volume :
- 29
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Circuits & Systems for Video Technology
- Publication Type :
- Academic Journal
- Accession number :
- 138481306
- Full Text :
- https://doi.org/10.1109/TCSVT.2017.2736599