Semi-automatic eyebrow recognition
Chenguang Zhang · Computer Engineering and Applications Journal · 2011
This paper proposes a semi-automatic eyebrow recognition method based on Hash Graph based Semi-supervised Learning(HGSL) and Support Vector Machines(SVMs).HGSL is presented to tackle the problem of time-consuming graph construction in Graph based Semi-supervised Learning method(GSL),for segmenting and extracting pure eyebrow images more efficiently in a semi-automatic way.The extracted pure eyebrow images are translated into feature vectors by Fourier transform and Gabor transform as well as principal component analysis,which are applied to training SVMs for recognition.On the BJUT eyebrow database,a series of experiments have been performed to analyze the effect of GSL and HGSL on eyebrow segmentation speed,and to summarize the influence of them together with feature and kernel selection on recognition rate.