Ear Biometrics Using 2D and 3D Images

Authors:
Ping Yan;KevinW. Bowyer
Affiliations:
University of Notre Dame;University of Notre Dame
Venue:
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Year:
2005

Citing 0
Cited 9

Human Ear Recognition in 3D

IEEE Transactions on Pattern Analysis and Machine Intelligence
Biometric Recognition Using 3D Ear Shape

IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Ear Recognition Approach for Personal Identification

ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Fusion of color spaces for ear authentication

Pattern Recognition
Efficient Detection and Recognition of 3D Ears

International Journal of Computer Vision
Automatic head and facial feature extraction based on geometry variations

Computer-Aided Design
A review of recent advances in 3D ear- and expression-invariant face biometrics

ACM Computing Surveys (CSUR)
A rotation and scale invariant technique for ear detection in 3D

Pattern Recognition Letters
3D pure ear extraction and recognition

CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present results of the largest experimental investigation of ear biometrics to date. Approaches considered include a PCA ("eigen-ear") approach with 2D intensity images, achieving 63.8% rank-one recognition; a PCA approach with range images, achieving 55.3% Hausdorff matching of edge images from range images, achieving 67.5%, and ICP matching of the 3D data, achieving 84.1%. ICP based matching not only achieves the best performance, but also shows good scalability with size of dataset. The data set used represents over 300 persons, each with images acquired on at least two different dates.