IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Human Face Recognition Using Point Signature
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face recognition: A literature survey
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CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Neighborhood Preserving Embedding
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Performance of Geometrix ActiveID^TM 3D Face Recognition Engine on the FRGC Data
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A 2D Range Hausdorff Approach for 3D Face Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Strategies and Benefits of Fusion of 2D and 3D Face Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Deformation Modeling for Robust 3D Face Matching
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combined 2D/3D Face Recognition Using Log-Gabor Templates
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Pose-encoded spherical harmonics for face recognition and synthesis using a single image
EURASIP Journal on Advances in Signal Processing
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Locality sensitive discriminant analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
3D model comparison using spatial structure circular descriptor
Pattern Recognition
3D face recognition with sparse spherical representations
Pattern Recognition
3D Face Recognition Using Simulated Annealing and the Surface Interpenetration Measure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regional registration for expression resistant 3-D face recognition
IEEE Transactions on Information Forensics and Security
3D Face Recognition Using Isogeodesic Stripes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Which parts of the face give out your identity?
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
A Region Ensemble for 3-D Face Recognition
IEEE Transactions on Information Forensics and Security
Less is More: Efficient 3-D Object Retrieval With Query View Selection
IEEE Transactions on Multimedia
RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Mandarin edutainment system integrated virtual learning environments
Speech Communication
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A robust sparse bounding sphere representation (RSBSR) is proposed to analyze 3D facial data. There are many obstacles to distinguishing facial differences, such as large pose and expression variations, hair occlusions and noise corruptions. In our framework, 3D point clouds are first preprocessed to remove the irrelevant areas and to align with a frontal neutral face model for overcoming the influence of large pose variations based on axis-angle representation. Then, 3D facial models are projected on the bounding spheres to describe both the depth and 3D geometric shape information, referred to as bounding sphere representation (BSR). This descriptor has the potential of decreasing the influence of large expression and pose variations on each normalized face within the corresponding spherical domain. Next, a robust group sparse regression model (RGSRM) is proposed to estimate the regression matrix, which preserves the intrinsic discriminant information. By embedding the descriptors into the low dimensional regression matrix, hair occlusions and artifacts can be treated as corruptions and can be patched. Under the constraints of Spectral Regression and corruptions, noise corruptions can be removed and the remaining small variations can be further corrected. FRGC v2.0 and CASIA 3D face databases are introduced to examine the performance of our framework and the previous algorithms with different schemes, and the experimental results show our proposed framework has the performance of simple implementation, high accuracy and low computational complexity.