Detecting faces from low-resolution images

Authors:
Shinji Hayashi;Osamu Hasegawa
Affiliations:
Tokyo Institute of Technology, Nagatsuta, Yokohama, Japan;Tokyo Institute of Technology, Nagatsuta, Yokohama, Japan
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Year:
2006

Citing 6
Cited 2

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FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition

Autonomous exploration using rapid perception of low-resolution image information

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IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning

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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.