Glasses removal from facial image using recursive error compensation

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...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2005-05, Vol.27 (5), p.805-811
Main Authors: Park, Jeong-Seon, Oh, You Hwa, Ahn, Sang Chul, Lee, Seong-Whan
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial Intelligence
Cluster Analysis
clustering algorithms
Computer Graphics
Computer science
control theory
systems
EM algorithm
Error compensation
Exact sciences and technology
Eyeglasses
Eyes
Face - anatomy & histology
Face detection
Face recognition
Facial
Feedback
Glass
Humans
Image Enhancement - methods
Image generation
Image Interpretation, Computer-Assisted - methods
Image reconstruction
Index Terms- Kernel methods
Information Storage and Retrieval - methods
K-Means
Numerical Analysis, Computer-Assisted
one class SVM
Pattern analysis
Pattern Recognition, Automated - methods
Pattern recognition. Digital image processing. Computational geometry
Principal component analysis
Recursive
Reflection
Reproducibility of Results
Robustness
Sensitivity and Specificity
Shape
Signal Processing, Computer-Assisted
Subtraction Technique
User-Computer Interface
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Summary: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.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2005.103