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Precise localization of eye centers with multiple cues

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Abstract

Automatic detection and precise localization of human eye centers are the essential processes in photo related multimedia applications. Since eye center points are used as reference base points for further intelligent processing, precise eye center localization is very important. In face recognition the accuracy of localization of eye centers directly influences the identification accuracy. A multiple stage approach with multiple cues for detection and precise localization of eye centers is presented in this paper. Multiple scopes searching strategy is used for correctly extracting eye patch images from the background. Dedicated gradient based features and curvelet based features are constructed and used for comprehensively revealing the intensity distribution characteristics and the edge based texture around eye centers. A rebuilt score calculation mechanism is proposed and the rebuilt scores are used as a specific measurement index reflecting the matching accuracy. The final localizations of eye centers are determined with integrating the gradient based scores and curvelet based scores. The experiment results testing on public face datasets show that the localization accuracy of proposed approach outperforms the accuracy with other state of the art methods.

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Acknowledgments

The research work is supported by the joint research funds of Dalian University of Technology and Shenyang Institute of Automation, Chinese Academy of Science. The authors would like to thank to those who provide public datasets which we used for training and testing, including the BioID Inc. for providing the BioID face dataset; Miyuki Kamachi, Michael Lyons and Jiro Gyoba for providing the JAFFE face dataset; the Face Recognition Group of JDL, ICT, CAS for providing the CAS-PEAL face dataset under the sponsors of National Hi-Tech Program and ISVISION Tech. Co. Ltd.

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Correspondence to Zongying Ou.

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Han, Z., Su, T., Ou, Z. et al. Precise localization of eye centers with multiple cues. Multimed Tools Appl 68, 931–945 (2014). https://doi.org/10.1007/s11042-012-1090-4

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