Semantic event representation and recognition using syntactic attribute graph grammar

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3D Human Activity Recognition with Reconfigurable Convolutional Neural Networks (2014, background): “Several compositional approaches were studied for complex scenarios and achieved substantial progresses[33, 29, 39, 21, 23, 30, 4, 15], and they decomposed an activity into deformable parts and enriched the models with contextual information.”
Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose (2016, background): “Later, the attribute grammar is adopted for action representations [18], [19], scene attribute tagging [20], and 3D scene construction from a single view [21].”
Video-Based Human Behavior Understanding: A Survey (2013, methodology): “[78] use attribute graphs for activity recognition.”
Learning latent spatio-temporal compositional model for human action recognition (2013, background): “Although many research studies [45, 41, 19, 46, 23, 5, 30, 37, 32, 8] have been carried out to understand and retrieve large scale video contents, these works focus on high level semantics instead of describing human activities.”