DocumentCode :
2861810
Title :
Automatic Eye Detection and Its Validation
Author :
Wang, Peng ; Green, Matthew B. ; Ji, Qiang ; Wayman, James
Author_Institution :
Rensselaer Polytechnic Institute
fYear :
2005
fDate :
25-25 June 2005
Firstpage :
164
Lastpage :
164
Abstract :
The accuracy of face alignment affects the performance of a face recognition system. Since face alignment is usually conducted using eye positions, an accurate eye localization algorithm is therefore essential for accurate face recognition. In this paper, we first study the impact of eye locations on face recognition accuracy, and then introduce an automatic technique for eye detection. The performance of our automatic eye detection technique is subsequently validated using FRGC 1.0 database. The validation shows that our eye detector has an overall 94.5% eye detection rate, with the detected eyes very close to the manually provided eye positions. In addition, the face recognition performance based on the automatic eye detection is shown to be comparable to that of using manually given eye positions.
Keywords :
Computer errors; Databases; Detectors; Eyes; Face detection; Face recognition; Pixel; Principal component analysis; Robustness; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on
Conference_Location :
San Diego, CA, USA
ISSN :
1063-6919
Print_ISBN :
0-7695-2372-2
Type :
conf
DOI :
10.1109/CVPR.2005.570
Filename :
1565482
Link To Document :
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