IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition without Correspondence using MultidimensionalReceptive Field Histograms
International Journal of Computer Vision
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Fast template matching using bounded partial correlation
Machine Vision and Applications
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 01
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eyebrow recognition: a new biometric technique
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Exploiting transitivity of correlation for fast template matching
IEEE Transactions on Image Processing
Effect of silhouette quality on hard problems in gait recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fast globally optimal algorithm for template matching using low-resolution pruning
IEEE Transactions on Image Processing
Identification of humans using gait
IEEE Transactions on Image Processing
Fast Template Matching With Polynomials
IEEE Transactions on Image Processing
Fast Template Matching Based on Normalized Cross Correlation With Adaptive Multilevel Winner Update
IEEE Transactions on Image Processing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
IJCB '11 Proceedings of the 2011 International Joint Conference on Biometrics
Hi-index | 0.00 |
This paper studies the problem of automatically recognizing human eyebrows using a frontal view. In the matching-recognizing framework for image-based object classification, we design an automatic human eyebrow recognition system via fast template matching and Fourier spectrum distance. Fast template matching is used to locate the target subregion of a gallery template or a pure eyebrow image in a probe original eyebrow image, whereas Fourier spectrum distance is used to determine the final identity of the probe original eyebrow image. We conducted a number of experiments to demonstrate the efficacy of the proposed system and corroborate the validity of eyebrow recognition on the BJUT eyebrow database. Moreover, we also tested the system on the color FERET database. Experimental results show that our approach can be directly applied to face recognition by only replacing eyebrow templates with face templates, and may achieve higher accuracy in eyebrow recognition than in small face recognition. This is a strong argument for eyebrow recognition to replace face recognition as an independent biometric in certain scenarios, especially where relatively large eyebrows can be cropped.