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Person re-identification combining deep features and attribute detection

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Watson, Gregory A. and Bhalerao, Abhir (2020) Person re-identification combining deep features and attribute detection. Multimedia Tools and Applications, 79 . pp. 6463-6481. doi:10.1007/s11042-019-08499-9

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Official URL: https://doi.org/10.1007/s11042-019-08499-9

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Abstract

Attributes-Based Re-Identification is a way of identifying individuals when presented with multiple pictures taken under varying conditions. The method typically builds a classifier to detect the presence of certain appearance characteristics in an image, and creates feature descriptors based on the output of the classifier. We improve attribute detection through spatial segregation of a person’s limbs using a skeleton prediction method. After a skeleton has been predicted, it is used to crop the image into three parts - top, middle and bottom. We then pass these images to an attribute prediction network to generate robust feature descriptors. We evaluate the performance of our method on the VIPeR, PRID2011 and i-LIDS data sets, comparing our results against the state-of-the-art to demonstrate competitive overall matching performance.

Item Type: Journal Article
Divisions: Faculty of Science > Computer Science
Journal or Publication Title: Multimedia Tools and Applications
Publisher: Springer
ISSN: 1380-7501
Official Date: March 2020
Dates:
DateEvent
March 2020Published
16 December 2019Available
19 November 2019Accepted
Date of first compliant deposit: 4 December 2019
Volume: 79
Page Range: pp. 6463-6481
DOI: 10.1007/s11042-019-08499-9
Status: Peer Reviewed
Publication Status: Published
Publisher Statement: This is a post-peer-review, pre-copyedit version of an article published in Multimedia Tools and Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11042-019-08499-9
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/L016400/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
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