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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Hayashi, S., Hasegawa, O. (2006). Detecting Faces from Low-Resolution Images. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_79
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DOI: https://doi.org/10.1007/11612032_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
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