Feature-based eye corner detection from static images

Haiying Xia; Guoping Yan

doi:10.1117/12.832837

30 October 2009 Feature-based eye corner detection from static images

Haiying Xia, Guoping Yan

Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 749619 (2009) https://doi.org/10.1117/12.832837
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Eye corner detection is important for eye extraction, face normalization, other facial landmark extraction and so on. We present a feature-based method for eye corner detection from static images in this paper. This method is capable of locating eye corners automatically. The process of eye corner detection is divided into two stages: classifier training and classifier application. For training, two classifiers trained by AdaBoost with Haar-like features, are skillfully designed to detect inner eye corners and outer eye corners. Then, two classifiers are applied to input images to search targets. Eye corners are finally located according to two eye models from targets. Experimental results tested on BioID face database and our own database demonstrate that our method obtains a high accuracy under clutter conditions.

Citation Download Citation

Haiying Xia and Guoping Yan "Feature-based eye corner detection from static images", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 749619 (30 October 2009); https://doi.org/10.1117/12.832837

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