Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28641
Title: Adaptive security for human surveillance using multimodal open set biometric recognition
Authors: Kumar, A
Kumar, A
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Proceedings - International Conference on Pattern Recognition, 2014, 6976789, p. 405-410 How to cite?
Abstract: In most human surveillance and forensic applications, key requirement is often to achieve highest possible true positive identification accuracy with a judicious compromise in accepting false positive identities. However with such scenario's in mind, there has been lack of any effort to develop adaptive security management for open set biometric recognition and most of the available prior work in literature has been focused on performance improvement for the rank-one recognition. This paper investigates the multimodal open set biometric recognition to address the conflicting requirements between the offered identification rate and high false positive identification rate while admitting possible unknown subjects/suspects in the higher rank (more than rank-one) list. The proposed approach attempts to offer accurate open set rank-K recognition which can automatically select a decision threshold to the desired/requested security level using ant colony optimization and provide a useful solution to a range of dynamic security problems in surveillance and high security applications. The performance evaluation of the proposed framework is ascertained through rigorous experimentation on three multimodal matchers from publicly available NIST BSSRlandXM2VTS databases.
Description: 22nd International Conference on Pattern Recognition, ICPR 2014, Sweden, 24-28 August 2014
URI: http://hdl.handle.net/10397/28641
ISBN: 978-1-4799-5209-0 (electronic)
978-1-4799-5210-6 (print on demand (PoD))
ISSN: 1051-4651
DOI: 10.1109/ICPR.2014.78
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