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Clothing and carrying condition invariant gait recognition based on rotation forest
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Das Choudhury, Sruti and Tjahjadi, Tardi (2016) Clothing and carrying condition invariant gait recognition based on rotation forest. Pattern Recognition Letters, 80 . pp. 1-7. doi:10.1016/j.patrec.2016.05.009 ISSN 0167-8655.
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Official URL: http://dx.doi.org/10.1016/j.patrec.2016.05.009
Abstract
This paper proposes a gait recognition method which is invariant to maximum number of challenging factors of gait recognition mainly unpredictable variation in clothing and carrying conditions. The method introduces an averaged gait key-phase image (AGKI) which is computed by averaging each of the five key-phases of the gait periods of a gait sequence. It analyses the AGKIs using high-pass and low-pass Gaussian filters, each at three cut-off frequencies to achieve robustness against unpredictable variation in clothing and carrying conditions in addition to other covariate factors, e.g., walking speed, segmentation noise, shadows under feet and change in hair style and ground surface. The optimal cut-off frequencies of the Gaussian filters are determined based on an analysis of the focus values of filtered human subject’s silhouettes. The method applies rotation forest ensemble learning recognition to enhance both individual accuracy and diversity within the ensemble for improved identification rate. Extensive experiments on public datasets demonstrate the efficacy of the proposed method.
Item Type: | Journal Article | ||||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||
Journal or Publication Title: | Pattern Recognition Letters | ||||||||||
Publisher: | Elsevier BV | ||||||||||
ISSN: | 0167-8655 | ||||||||||
Official Date: | 1 September 2016 | ||||||||||
Dates: |
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Volume: | 80 | ||||||||||
Page Range: | pp. 1-7 | ||||||||||
DOI: | 10.1016/j.patrec.2016.05.009 | ||||||||||
Status: | Peer Reviewed | ||||||||||
Publication Status: | Published | ||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||
Date of first compliant deposit: | 26 May 2016 | ||||||||||
Date of first compliant Open Access: | 24 May 2017 | ||||||||||
Adapted As: |
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