Robust facial expression recognition using local binary patterns

By Caifeng Shan, Shaogang Gong, Peter W. McOwan. IEEE International Conference on Image Processing 2005, 2005

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Facial expression recognition based on Local Binary Patterns: A comprehensive study (2009, methodology): “LBP features were previously used for facial expression classiﬁ-cation in [31], and more recently, following our work [33], Liao et al. [34] presented an extended LBP operator to extract features for facial expression recognition.”
Facial Expression Recognition With Visual Transformers and Attentional Selective Fusion (2021, background): “Gradients (HOGs)[3], Local Binary Patterns (LBP)[4],[5], non-negative matrix factorization (NMF)[6] and sparse representation[7]).”
Facial expression recognition using radial encoding of local Gabor features and classifier synthesis (2012, result): “If we compare our results to those for seven classes which include the neutral face [12,54], our recognition accuracy of 91.”
Automatic facial expression recognition using features of salient facial patches (2015, methodology): “—————————— ——————————”
Robust Facial Expression Recognition Based on Local Directional Pattern (2010, background): “Shan and others [2] used this variant of the LBP, which has at most two transitions (LBP), for their facial”