Designing a Low-Resolution Face Recognition System for Long-Range Surveillance

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    Most face recognition systems deal well with high-resolution facial images, but perform much worse on low-resolution facial images. In low-resolution face recognition, there is a specific but realistic surveillance scenario: a surveillance camera monitoring a large area. In this scenario, usually the gallery images are of high-resolution and the probe images are of various low-resolutions depending on the distances between the subject and the camera. In this paper, we design a low-resolution face recognition system for this scenario. We use a state-of-the-art mixed-resolution classifier to deal with the resolution mismatch between the gallery and probe images. We also set up experiments to explore the best training configuration for probe images of various resolutions. Our experimental results show that one classifier which is trained on images of various resolutions covering the whole range has promising results in the long-range surveillance scenario. This system has at least as good performance as combining multiple face recognition systems that are optimised for different resolutions.
    Original languageUndefined
    Number of pages5
    Publication statusPublished - 21 Sept 2016
    Event15th International Conference of the Biometrics Special Interest Group, BIOSIG 2016 - Darmstadt, Germany, Darmstadt, Germany
    Duration: 21 Sept 201623 Sept 2016
    Conference number: 15


    Conference15th International Conference of the Biometrics Special Interest Group, BIOSIG 2016
    Abbreviated titleBIOSIG 2016
    Other21-23 Sep 2016


    • resolution mismatch
    • EWI-27637
    • IR-104052
    • low-resolution face recognition system
    • SCS-Safety
    • long-range surveillance

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