Mudunuri, Sivaram Prasad and Venkataramanan, Shashanka and Biswas, Soma (2019) Dictionary Alignment With Re-Ranking for Low-Resolution NIR-VIS Face Recognition. In: IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 14 (4). pp. 886-896.
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Abstract
Recently, near-infrared (NIR) images are increasingly being captured for recognizing faces in low-light/nighttime conditions. Matching these images against the controlled high-resolution visible facial images usually present in the database is a challenging task. In surveillance scenarios, the NIR images can have very low resolution and also non-frontal pose which makes the problem even more challenging. In this paper, we propose an orthogonal dictionary alignment approach for addressing this problem. We also propose a re-ranking approach to further improve the recognition performance for each probe by combining the rank list given by the proposed algorithm with that given by another complementary feature/algorithm. Finally, we have also collected our own database Heterogeneous face recognition across Pose and Resolution (HPR) that has facial images captured from two surveillance quality NIR cameras and one high-resolution visible camera, with significant variations in head pose and resolution. Extensive experiments on the modified CASIA NIR-VIS 2.0 database, the Surveillance Camera face database, and our HPR database show the effectiveness of the proposed approaches and the collected database.
Item Type: | Journal Article |
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Publication: | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY |
Publisher: | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
Additional Information: | Copy right for this article belong to IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
Keywords: | Heterogeneous face recognition; re-ranking; low-resolution; head pose |
Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
Date Deposited: | 19 Nov 2018 14:42 |
Last Modified: | 19 Nov 2018 14:42 |
URI: | http://eprints.iisc.ac.in/id/eprint/61092 |
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