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Deep Cosine Metric Learning for Person Re-Identification

Wojke, Nicolai and Bewley, Alex (2018) Deep Cosine Metric Learning for Person Re-Identification. In: Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017. IEEE. IEEE Winter Conference on Applications of Computer Vision (WACV), 2018-03-12 - 2018-03-14, Lake Tahoe, NV/CA. doi: 10.1109/WACV.2018.00087.

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Metric learning aims to construct an embedding where two extracted features corresponding to the same identity are likely to be closer than features from different identities. This paper presents a method for learning such a feature space where the cosine similarity is effectively optimized through a simple re-parametrization of the conventional softmax classification regime. At test time, the final classification layer can be stripped from the network to facilitate nearest neighbor queries on unseen individuals using the cosine similarity metric. This approach presents a simple alternative to direct metric learning objectives such as siamese networks that have required sophisticated pair or triplet sampling strategies in the past. The method is evaluated on two large-scale pedestrian re-identification datasets where competitive results are achieved overall. In particular, we achieve better generalization on the test set compared to a network trained with triplet loss.

Item URL in elib:https://elib.dlr.de/116408/
Document Type:Conference or Workshop Item (Speech)
Title:Deep Cosine Metric Learning for Person Re-Identification
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Journal or Publication Title:Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:Person Re-Identification, Metric Learning, Convolutional Neural Networks
Event Title:IEEE Winter Conference on Applications of Computer Vision (WACV)
Event Location:Lake Tahoe, NV/CA
Event Type:international Conference
Event Start Date:12 March 2018
Event End Date:14 March 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - I.MoVe (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Data Management and Knowledge Discovery
Deposited By: Wojke, Nicolai
Deposited On:19 Dec 2017 14:50
Last Modified:24 Apr 2024 20:20

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