Reconstruction of Partially Damaged Face Images Based on a Morphable Face Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Multidimensional Morphable Models
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Automatic Eyeglasses Removal from Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Glasses Removal from Facial Image Using Recursive Error Compensation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal component analysis for facial animation
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Journal of Cognitive Neuroscience
Occlusion, attention and object representations
Integrated Computer-Aided Engineering - Artificial Neural Networks
View invariant head recognition by Hybrid PCA based reconstruction
Integrated Computer-Aided Engineering
Asymmetric Principal Component and Discriminant Analyses for Pattern Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
Automatic image search based on improved feature descriptors and decision tree
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering
Occlusion invariant face recognition using selective LNMF basis images
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Integrated Computer-Aided Engineering
Pedestrian detection in far infrared images
Integrated Computer-Aided Engineering
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When only non-occluded image parts are available for facial images it is difficult or impossible to correctly recognize the person in the image. The problem addressed in this work is reconstruction of the occluded parts in facial images; e.g. eyes covered with sunglasses. Asymmetrical Principal Component Analysis aPCA allows estimation of occluded facial parts based on the content of the facial parts which are visible. aPCA is used to estimate full non-occluded faces from 3 kinds of occlusion with 2 different reconstruction methods in this work and we present the results with both objective and subjective evaluation. The subjective evaluation shows that clear and sharp image regions are preferred even if this results in visible edges in the images. The method also performs well when a different facial expression than the one in the database is used to calculate the reconstruction parameters.