Paper Info
Title
Eye Detection Based on Skin Color Analysis with Different Poses under Varying Illumination Environment
Abstract
In this paper, we propose a method of eye detection based on skin color analysis under varying illumination. The proposed method consists of several phases, including color conversion, skin color segmentation and face mask calculation, facial feature extraction and eye candidate determination, and detection of human eyes. To eliminate the effect of lighting change on the performance of eye detection, color conversion is first performed. Face mask calculation based on skin color segmentation is then carried out to reduce the possible searching region of human eyes. Eye candidates detected using facial features are used to define the possible human eyes. Human eyes are thus detected by the geometric features of gravity and spatial centers for these eye candidates. Results show that the proposed method works well for faces with different poses and multiple faces under varying illumination. The eye detection time of 21.8 ms is achieved for an image of size 213×320 pixels, indicating computational efficiency of the proposed system.
Year
DOI
Venue
2011
10.1109/ICGEC.2011.65
ICGEC
Keywords
Field
DocType
illumination environment,human eye detection,eye detection time,skin color analysis,eye detection,human eye,varying illumination,image segmentation,color space,face mask calculation,varying illumination environment,eye candidate,feature extraction,eye candidate determination,object detection,facial feature extraction,skin color segmentation,color conversion,different poses,image colour analysis,lighting,face,skin
Object detection,Computer vision,Color space,Computer science,Segmentation,Feature extraction,Image segmentation,Color analysis,Artificial intelligence,Pixel,Eye detection
Conference
ISBN
Citations 
PageRank 
978-0-7695-4449-6
1
0.36
References 
Authors
3
4
Name
Order
Citations
PageRank
Deng-Yuan Huang116315.28
Ta-Wei Lin2544.58
Wu-Chih Hu324427.01
Mu-Song Chen4588.66