Video-Based Person Re-Identification by Simultaneously Learning Intra-Video and Inter-Video Distance Metrics
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 3552-3558.
Abstract
Video-based person re-identification (re-id) is an important application in practice. However, only a few methods have been presented for this problem. Since large variations exist between different pedestrian videos, as well as within each video, it's challenging to conduct re-identification between pedestrian videos. In this paper, we propose a simultaneous intra-video and inter-video distance learning (SI2DL) approach for video-based person re-id. Specifically, SI2DL simultaneously learns an intra-video distance metric and an inter-video distance metric from the training videos. The intra-video distance metric is to make each video more compact, and the inter-video one is to make that the distance between two truly matching videos is smaller than that between two wrong matching videos. To enhance the discriminability of learned metrics, we design a video relationship model, i.e., video triplet, for SI2DL. Experiments on the public iLIDS-VID and PRID 2011 image sequence datasets show that our approach achieves the state-of-the-art performance.
@inproceedings{ijcai2016p501,
title = {Video-Based Person Re-Identification by Simultaneously Learning Intra-Video and Inter-Video Distance Metrics},
author = {Zhu, Xiaoke and Jing, Xiao-Yuan and Wu, Fei and Feng, Hui},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {3552--3558},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/501},
}
TY - CPAPER TI - Video-Based Person Re-Identification by Simultaneously Learning Intra-Video and Inter-Video Distance Metrics AU - Zhu, Xiaoke AU - Jing, Xiao-Yuan AU - Wu, Fei AU - Feng, Hui T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 3552 EP - 3558 UR - https://ijcai.org/proceedings/2016/501 ER -Copied
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