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Dictionary Alignment With Re-Ranking for Low-Resolution NIR-VIS Face Recognition

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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Official URL: http://dx.doi.org/10.1109/TIFS.2018.2868173


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
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
Depositing User: Id for Latest eprints
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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