Title :
Glasses removal from facial image using recursive error compensation
Author :
Park, Jeong-Seon ; Oh, You Hwa ; Ahn, Sang Chul ; Lee, Seong-Whan
Author_Institution :
Dept. of Comput. Sci. & Eng., Korea Univ., Seoul, South Korea
fDate :
5/1/2005 12:00:00 AM
Abstract :
In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.
Keywords :
error compensation; face recognition; hidden feature removal; principal component analysis; PCA reconstruction; face recognition system; glasses occlusion; human frontal facial image; principal component analysis; recursive error compensation; Error compensation; Eyes; Face detection; Face recognition; Glass; Image generation; Image reconstruction; Principal component analysis; Robustness; Shape; EM algorithm; Index Terms- Kernel methods; K-Means.; clustering algorithms; one class SVM; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Graphics; Eyeglasses; Face; Feedback; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; User-Computer Interface;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2005.103