Local feature based 3d face recognition

Authors:
Yonguk Lee;Hwanjong Song;Ukil Yang;Hyungchul Shin;Kwanghoon Sohn
Affiliations:
Biometrics Engineering Research Center, Department of Electrical & Electronics Engineering, Yonsei University, Seoul, Korea;Biometrics Engineering Research Center, Department of Electrical & Electronics Engineering, Yonsei University, Seoul, Korea;Biometrics Engineering Research Center, Department of Electrical & Electronics Engineering, Yonsei University, Seoul, Korea;Biometrics Engineering Research Center, Department of Electrical & Electronics Engineering, Yonsei University, Seoul, Korea;Biometrics Engineering Research Center, Department of Electrical & Electronics Engineering, Yonsei University, Seoul, Korea
Venue:
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Year:
2005

Citing 5
Cited 8

Support Vector Machines for 3D Object Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Two- and three-dimensional patterns of the face

Two- and three-dimensional patterns of the face
Robust Face Recognition Using Dynamic Space Warping

ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
Face Recognition by Support Vector Machines

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face Modeling and Recognition in 3-D

AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures

A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition

Computer Vision and Image Understanding
The 3DID face alignment system for verifying identity

Image and Vision Computing
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition

Computer Vision and Image Understanding
Pose robust 3D face recognition using the RBFN feature

VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Anthropometric 3D Face Recognition

International Journal of Computer Vision
Brief description of image based 3D face recognition methods

3D Research
Hybrid face recognition based on real-time multi-camera stereo-matching

ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
3D human face description: landmarks measures and geometrical features

Image and Vision Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a 3D face recognition system based on geometrically localized facial features. We propose the feature extraction procedure using the geometrical characteristics of a face. We extract three curvatures, eight invariant facial feature points and their relative features. These features are directly applied to face recognition algorithms which are a depth-based DP (Dynamic Programming) and a feature-based SVM (Support Vector Machine). Experimental results show that face recognition rates based on the depth-based DP and the feature-based SVM are 95% for 20 people and 96% for 100 people, respectively.