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http://dx.doi.org/10.9717/kmms.2012.15.5.606

Inclined Face Detection using JointBoost algorithm  

Jung, Youn-Ho (충남대학교 메카트로닉스공학과)
Song, Young-Mo (LG전자)
Ko, Yun-Ho (충남대학교 메카트로닉스공학과)
Publication Information
Journal of Korea Multimedia Society / v.15, no.5, 2012 , pp. 606-614 More about this Journal
Abstract
Face detection using AdaBoost algorithm is one of the fastest and the most robust face detection algorithm so many improvements or extensions of this method have been proposed. However, almost all previous approaches deal with only frontal face and suffer from limited discriminant capability for inclined face because these methods apply the same features for both frontal and inclined face. Also conventional approaches for detecting inclined face which apply frontal face detecting method to inclined input image or make different detectors for each angle require heavy computational complexity and show low detection rate. In order to overcome this problem, a method for detecting inclined face using JointBoost is proposed in this paper. The computational and sample complexity is reduced by finding common features that can be shared across the classes. Simulation results show that the detection rate of the proposed method is at least 2% higher than that of the conventional AdaBoost method under the learning condition with the same iteration number. Also the proposed method not only detects the existence of a face but also gives information about the inclined direction of the detected face.
Keywords
face detection; JointBoost; AdaBoost; shared feature; inclined face;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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