A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking
Abstract
Automatic 2.5D face landmarking aims at locating facial feature points on 2.5D face models, such as eye corners, nose tip, etc. and has many applications ranging from face registration to facial expression recognition. In this paper, we propose a rotation invariant 2.5D face landmarking solution based on facial curvature analysis combined with a generic 2.5D face model and make use of a coarse-to-fine strategy for more accurate facial feature points localization. Experimented on more than 1600 face models randomly selected from the FRGC dataset, our technique displays, compared to a ground truth from a manual 3D face landmarking, a 100% of good nose tip localization in 8 mm precision and 100% of good localization for the eye inner corner in 12 mm precision.
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Overview of the Face Recognition Grand Challenge
Phillips, P. J., Flynn, P. J., Scruggs, T., Bowyer, K. W., Chang, J., Hoffman, K., Marques, J., Min, J., & Worek, W. J. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2005.268 · Cited by 2,493 · see citing works
Least-squares estimation of transformation parameters between two point patterns
Umeyama, S. (1991) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.88573 · Cited by 2,429 · see citing works
Introductory Techniques for 3-D Computer Vision
Trucco, E., & Verri, A. (1998) · Medical Entomology and Zoology · Cited by 1,900 · see citing works
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Bowyer, K. W., Chang, K. J., & Flynn, P. J. (2005) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2005.05.005 · Cited by 982 · see citing works
Estimating 3-D rigid body transformations: a comparison of four major algorithms
Eggert, D. W., Lorusso, A., & Fisher, R. B. (1997) · Machine Vision and Applications · doi:10.1007/s001380050048 · Cited by 808 · see citing works
Invariant surface characteristics for 3D object recognition in range images
Besl, P. J., & Jain, R. (1986) · Computer Vision Graphics and Image Processing · doi:10.1016/0734-189x(86)90220-3 · Cited by 517 · see citing works
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
Mian, A. S., Bennamoun, M., & Owens, R. A. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1105 · Cited by 469 · see citing works
Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression
Chang, K. I., Bowyer, K. W., & Flynn, P. J. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.210 · Cited by 362 · see citing works
3D face detection using curvature analysis
Colombo, A., Cusano, C., & Schettini, R. (2006) · Pattern Recognition · doi:10.1016/j.patcog.2005.09.009 · Cited by 229 · see citing works
Three-Dimensional Model Based Face Recognition
Lu, X., Colbry, D., & Jain, A. K. (2004) · Cited by 130 · see citing works
Detection of Anchor Points for 3D Face Veri.cation
Colbry, D., Stockman, G. C., & Jain, A. (2006) · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvpr.2005.441 · Cited by 118 · see citing works
Automatic Feature Extraction for Multiview 3D Face Recognition
Lu, X., & Jain, A. K. (2006) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fgr.2006.23 · Cited by 116 · see citing works
Three-dimensional model based face recognition
Lu, X., Colbry, D., & Jain, A. K. (2004) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2004.1334127 · Cited by 106 · see citing works
Face recognition using 3D local geometrical features: PCA vs. SVM
Moreno, A. B., Sánchez, Á., Vélez, J. F., et al. (2005) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa.2005.195407 · Cited by 74 · see citing works
Rotated Profile Signatures for robust 3D feature detection
Faltemier, T. C., Bowyer, K. W., & Flynn, P. J. (2008) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2008.4813413 · Cited by 57 · see citing works
Automatic pose estimation of 3D facial models
Sun, Y., & Yin, L. (2008) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2008.4760973 · Cited by 54 · see citing works
Precise Localization of Landmarks on 3D Faces using Gabor Wavelets
D’Hose, J., Colineau, J., Bichon, C., et al. (2007) · IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) · doi:10.1109/btas.2007.4401927 · Cited by 41 · see citing works
Automated Facial Feature Detection from Portrait and Range Images
Jahanbin, S., Bovik, A. C., & Choi, H. (2008) · IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) · doi:10.1109/ssiai.2008.4512276 · Cited by 28 · see citing works
Least-squares fitting of multiple M-dimensional point sets
Wen, G., Wang, Z., Xia, S., et al. (2006) · The Visual Computer · doi:10.1007/s00371-006-0022-6 · Cited by 20 · see citing works
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Corneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527 · see citing works
- Authors
- Szeptycki, P., Ardabilian, M., & Chen, L.
- Affiliations
- École Centrale de Lyon (FR)
- Venue
- 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems
- Publisher
- IEEE
- Published
- 2009-09
- Pages
- 1-6
- OpenAlex
- W2091182651
- Cited by
- 101
- References
- 19
- Citations by year
- 2025: 1 · 2024: 1 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 7 · 2018: 5 · 2017: 11 · 2016: 7 · 2015: 8 · 2014: 14 · 2013: 11 · 2012: 15
- FWCI
- 8.16
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) (publishedVersion)
- HAL (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- rotation invariance, coarse-to-fine localization
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