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Person re-identification using deep foreground appearance modeling
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Watson, Gregory A. and Bhalerao, Abhir (2018) Person re-identification using deep foreground appearance modeling. Journal of Electronic Imaging, 27 (05). 051215. doi:10.1117/1.jei.27.5.051215 ISSN 1017-9909.
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Official URL: https://doi.org/10.1117/1.JEI.27.5.051215
Abstract
Person reidentification is the process of matching individuals from images taken of them at different times and often with different cameras. To perform matching, most methods extract features from the entire image; however, this gives no consideration to the spatial context of the information present in the image. We propose using a convolutional neural network approach based on ResNet-50 to predict the foreground of an image: the parts with the head, torso, and limbs of a person. With this information, we use the LOMO and salient color name feature descriptors to extract features primarily from the foreground areas. In addition, we use a distance metric learning technique (XQDA), to calculate optimally weighted distances between the relevant features. We evaluate on the VIPeR, QMUL GRID, and CUHK03 data sets and compare our results against a linear foreground estimation method, and show competitive or better overall matching performance.
Item Type: | Journal Article | ||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
SWORD Depositor: | Library Publications Router | ||||||
Library of Congress Subject Headings (LCSH): | Pattern recognition systems, Computer vision, Biometric identification, Neural networks (Computer science), Image registration | ||||||
Journal or Publication Title: | Journal of Electronic Imaging | ||||||
Publisher: | SPIE-Intl Soc Optical Eng | ||||||
ISSN: | 1017-9909 | ||||||
Official Date: | 2 April 2018 | ||||||
Dates: |
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Volume: | 27 | ||||||
Number: | 05 | ||||||
Article Number: | 051215 | ||||||
DOI: | 10.1117/1.jei.27.5.051215 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 17 April 2018 | ||||||
Date of first compliant Open Access: | 17 April 2018 | ||||||
RIOXX Funder/Project Grant: |
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