Moving Poselets: A Discriminative and Interpretable Skeletal Motion Representation for Action Recognition

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Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, background): “Tao and Vidal [210] Moving Poselets BoW Body Dict X Eweiwi et al.”
Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks (2017, neutral): “nition have been proposed [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41].”
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates (2017, neutral): “Skeleton-based action recognition has been explored in different aspects in recent years [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57].”
A Hierarchical Pose-Based Approach to Complex Action Understanding Using Dictionaries of Actionlets and Motion Poselets (2016, methodology): “We refer to the components of this dictionary as motion poselets [2, 26].”
Global Context-Aware Attention LSTM Networks for 3D Action Recognition (2017, background): “Various feature extractors and classifier learning methods for 3D action recognition have been proposed in the past few years [28, 37, 31, 65, 54, 26, 34, 5, 47, 59, 38, 56, 32, 2].”
RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos (2017, methodology): “One well-known pose-based representation is poselet [2] which has been applied to action recognition and detection in videos [34, 44, 52].”