Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
A clustering algorithm based on maximal θ-distant subtrees
Pattern Recognition
Deformable templates for face recognition
Journal of Cognitive Neuroscience
A separable low complexity 2D HMM with application to face recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic gait recognition based on statistical shape analysis
IEEE Transactions on Image Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Human eyebrow recognition in the matching-recognizing framework
Computer Vision and Image Understanding
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Eyebrow is presented as a new biometric for personal identification. Based on feature strings which are extracted from eyebrow images, an eyebrow recognition method is described in detail and analyzed in experiments on a small eyebrow database taken from 32 persons. The results have shown that the presented method can reach the highest accuracies of 93.75% and 90.63% as well as the lowest accuracies of 87.50% and 81.25%, respectively, in two small-scale experiments. Since the recognition accuracies may be higher by improving the current method or introducing other ones, eyebrow is likely to work as a good biometric in the future.