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    Detecting Faces from Low-Resolution Images

    Detecting Faces from Low-Resolution Images


    Abstract Face detection is a hot research topic in Computer Vision; the field has greatly progressed over the past decade. However, to our knowledge, face detection in low-resolution images has not been studied. In this paper, we use a conventional AdaBoost-based face detector to show that the face detection rate falls to 39% from 88% as face resolution decreases from 24 × 24 pixels to 6 × 6 pixels. We propose a new face detection method comprising four techniques. As a result, our method improved the face detection rate from 39% to 71% for 6 × 6 pixel faces of MIT+CMU frontal face test set. We also show our method can detect 6×6 faces in real scene other than MIT+CMU frontal face test set.

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    Titel :

    Detecting Faces from Low-Resolution Images

    Beteiligte:
    Hayashi, Shinji (Autor:in) / Hasegawa, Osamu (Autor:in)
    Erschienen in:

    Computer Vision – ACCV 2006 ; 10 ; 787-796

    Lecture Notes in Computer Science ; 3851 , 10

    Erscheinungsdatum :

    2006-01-01

    Format / Umfang :

    10 pages

    ISBN :

    978-3-540-32433-1 , 978-3-540-31219-2

    ISSN :

    0302-9743 , 1611-3349

    DOI :

    https://doi.org/10.1007/11612032_79

    Medientyp :

    Aufsatz/Kapitel (Buch)

    Format :

    Elektronische Ressource

    Sprache :

    Englisch

    Schlagwörter :

    Input Image , Face Image , Face Detection , Weak Learner , Face Size Computer Science , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Image Processing and Computer Vision , Artificial Intelligence (incl. Robotics) , Algorithm Analysis and Problem Complexity

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