Recognition of faces in unconstrained environments: a comparative study
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
On the Spatial Distribution of Local Non-parametric Facial Shape Descriptors
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
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In this paper, we present a new LBP-based face recognition method with Hamming distance constraint. The traditional LBP operator uses a uniform pattern to describe the local features and assort the other nonuniform patterns to one additional class, for images under expression and illumination condition changes, this method could cause more inaccuracy and instability. By assuming that the illumination, pose or expression changes of a face image are some kinds of "noise", we introduce the widely used Hamming distance in channel coding to LBP so as to decrease the error rate caused by these noise disturbances. Experimental results on FRGC show that our method improves the recognition performance obviously than the traditional LBP-based face recognition methods when face images are under uncontrolled circumstances.