In this paper, we propose volume based local Gabor binary patterns (V-LGBP) for face representation and recognition. In our method, the Gabor feature set of each gray image is regarded as a three dimensional "volume", where the first two dimensions are spatial domain and the third dimension is the Gabor filter index. Then, the neighborhood order relationship in the "volume" is encoded by Local Binary Patterns (LBP), which converts the Gabor transformed images into multiple index maps. Finally, the spatial histograms of all the V-LGBP index maps are concatenated together to represent the facial appearances. In addition, in order to reflect the uniform appearances of V-LGBP, its uniform patterns are redefined via statistical analysis. Extensive experiments on FERET dataset validate the effectiveness of our approach.
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