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At-a-distance person recognition via combining ocular features
S. Verma, P. Mittal, ,
Published in IEEE Computer Society
Volume: 2016-August
Pages: 3131 - 3135
Person recognition is a challenging research problem particularly if the images are captured at a distance and only ocular region is present. In this research, we present a framework that extracts multiple features from iris and periocular regions from near infrared images captured at a distance of 2 meters or more. Using these features and random decision forest, fusion and classification is performed and verification results are reported. On CASIA V4-at-a-distance and FOCS databases, the proposed algorithm yields state-of-the-art results; particularly achieving over 61% genuine accept rate at 0.1% false accept rate on complete CASIA V4-at-a-distance database. © 2016 IEEE.
About the journal
JournalData powered by TypesetProceedings - International Conference on Image Processing, ICIP
PublisherData powered by TypesetIEEE Computer Society