A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Feature-based correspondence: an eigenvector approach
Image and Vision Computing - Special issue: BMVC 1991
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
SMI '04 Proceedings of the Shape Modeling International 2004
A Survey Of Approaches To Three-Dimensional Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Three-Dimensional Face Recognition
International Journal of Computer Vision
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Combining local features for robust nose location in 3D facial data
Pattern Recognition Letters
Description and retrieval of 3D face models using iso-geodesic stripes
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
A spectral approach to shape-based retrieval of articulated 3D models
Computer-Aided Design
Adapting Geometric Attributes for Expression-Invariant 3D Face Recognition
SMI '07 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2007
Retrieving articulated 3-D models using medial surfaces
Machine Vision and Applications
Numerical Geometry of Non-Rigid Shapes
Numerical Geometry of Non-Rigid Shapes
Bosphorus Database for 3D Face Analysis
Biometrics and Identity Management
3D Face Recognition using Euclidean Integral Invariants Signature
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids
Computer-Aided Design
Plastic surgery 1, face recognition 0
IEEE Spectrum
Expression-invariant 3D face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
International Journal of Computer Vision
Robust expression-invariant face recognition from partially missing data
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
3-D Face Recognition With the Geodesic Polar Representation
IEEE Transactions on Information Forensics and Security - Part 2
On bending invariant signatures for surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Expression-Invariant Representations of Faces
IEEE Transactions on Image Processing
SHREC'10 track: non-rigid 3D shape retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC'11 track: shape retrieval on non-rigid 3D watertight meshes
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
Computer Vision and Image Understanding
SMI 2013: Grouping real functions defined on 3D surfaces
Computers and Graphics
CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
Machine Vision and Applications
Hi-index | 0.01 |
Intra-shape deformations complicate 3D shape recognition and therefore need proper modeling. Thereto, an isometric deformation model is used in this paper. The method proposed does not need explicit point correspondences for the comparison of 3D shapes. The geodesic distance matrix is used as an isometry-invariant shape representation. Two approaches are described to arrive at a sampling order invariant shape descriptor: the histogram of geodesic distance matrix values and the set of largest singular values of the geodesic distance matrix. Shape comparison is performed by comparison of the shape descriptors using the @g^2-distance as dissimilarity measure. For object recognition, the results obtained demonstrate the singular value approach to outperform the histogram-based approach, as well as the state-of-the-art multidimensional scaling technique, the ICP baseline algorithm and other isometric deformation modeling methods found in literature. Using the TOSCA database, a rank-1 recognition rate of 100% is obtained for the identification scenario, while the verification experiments are characterized by a 1.58% equal error rate. External validation demonstrates that the singular value approach outperforms all other participants for the non-rigid object retrieval contests in SHREC 2010 as well as SHREC 2011. For 3D face recognition, the rank-1 recognition rate is 61.9% and the equal error rate is 11.8% on the BU-3DFE database. This decreased performance is attributed to the fact that the isometric deformation assumption only holds to a limited extent for facial expressions. This is also demonstrated in this paper.