NDLI: Cross-view gait recognition by fusion of multiple transformation consistency measures

Content Provider	IET Digital Library
Author	Muramatsu, Daigo Makihara, Yasushi Yagi, Yasushi
Abstract	Gait is a promising modality for forensic science because it has discrimination ability even if the gait features are extracted from low-quality image sequences captured at a distance. However, in forensic cases the observation view is often different, leading to accuracy degradation. Therefore the authors propose a gait recognition algorithm that achieves high accuracy in cases where observation views are different. They used a view transformation technique, and generated multiple joint gait features by changing the source gait features. They formed a hypothesis that the multiple transformed features and original features should be similar to each other if the target subjects are the same. They calculated multiple scores that measured the consistency of the features, and a likelihood ratio from the scores. To evaluate the accuracy of the proposed method, they drew Tippett plots and empirical cross-entropy plots, together with cumulative match characteristic curves and receiver operator characteristic curves, and evaluated discrimination ability and calibration quality. The results showed that their proposed method achieves good results in terms of discrimination and calibration.
Starting Page	62
Ending Page	73
Page Count	12
ISSN	20474938
Volume Number	4
e-ISSN	20474946
Issue Number	Issue 2, Jun (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/4/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2014.0042
Journal	IET Biometrics
Publisher Date	2015-03-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Calibration Calibration Quality Computer Vision And Image Processing Technique Cross-view Gait Recognition Cumulative Match Characteristic Curves Data Security Digital Forensics Discrimination Ability Empirical Cross-entropy Plots Feature Extraction Forensic Science Gait Analysis Gait Feature Extraction Gait Recognition Algorithm Image Recognition Image Sequence Low-quality Image Sequence Receiver Operator Characteristic Curves Sensitivity Analysis Tippett Plots Transformation Consistency Measures View Transformation Technique
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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