Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines

By Irene Kotsia, Ioannis Pitas. IEEE Transactions on Image Processing, 2007

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Face Expression Recognition and Analysis: The State of the Art (2012, background): “Also, sadness was confused with anger [19], [21], [22], [23], [25].”
Fully Automatic Recognition of the Temporal Phases of Facial Actions (2012, neutral): “, [13]–[16]).”
Facial Expression Analysis (2011, background): “tive shape model [20, 22, 61], or face component shape parametrization [111].”
Local Directional Number Pattern for Face Analysis: Face and Expression Recognition (2013, background): “The former [4], [5] encodes the shape and locations of different facial components, which are combined into a feature vector that represents the face.”
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-related Applications (2016, methodology): “Many methods focus on recognizing a limited set of primary emotions (usually 6) [115], [116], [123], [130], [137],”