Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Radon representation-based feature descriptor for texture classification
IEEE Transactions on Image Processing
Texture analysis and classification using deterministic tourist walk
Pattern Recognition
Maximum margin distance learning for dynamic texture recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Face recognition based on combination of human perception and local binary pattern
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Translation Invariance in the Polynomial Kernel Space and Its Applications in kNN Classification
Neural Processing Letters
Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks
Expert Systems with Applications: An International Journal
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Dynamic texture is an extension of texture to the temporal domain. In this paper, a new method for recognizing dynamic textures is proposed. The textures are modeled with concatenated local binary patterns in three orthonormal planes. The circular neighborhoods are generalized to elliptical sampling to fit to the space-time statistics. This is an extension of the LBP approach widely used in still texture analysis, combining the motion and appearance together. Our approach has many advantages compared with the earlier approaches providing a better performance for the DynTex and MIT databases.