Human action recognition: A taxonomy-based survey, updates, and opportunities
Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …
accurately identify and interpret human actions. One of the most challenging issues for …
A review of machine learning-based human activity recognition for diverse applications
Human activity recognition (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …
computer science. Due to the articulated nature of human motion, it is not trivial to detect …
Vision-based human activity recognition: a survey
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …
human activities using acquired information from various types of sensors. Although several …
Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding
Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …
demonstrated the effectiveness of 3D representation for action recognition. The existing …
Point 4d transformer networks for spatio-temporal modeling in point cloud videos
Point cloud videos exhibit irregularities and lack of order along the spatial dimension where
points emerge inconsistently across different frames. To capture the dynamics in point cloud …
points emerge inconsistently across different frames. To capture the dynamics in point cloud …
Spatio-temporal lstm with trust gates for 3d human action recognition
Abstract 3D action recognition–analysis of human actions based on 3D skeleton data–
becomes popular recently due to its succinctness, robustness, and view-invariant …
becomes popular recently due to its succinctness, robustness, and view-invariant …
Ntu rgb+ d: A large scale dataset for 3d human activity analysis
Recent approaches in depth-based human activity analysis achieved outstanding
performance and proved the effectiveness of 3D representation for classification of action …
performance and proved the effectiveness of 3D representation for classification of action …
Enhanced skeleton visualization for view invariant human action recognition
Human action recognition based on skeletons has wide applications in human–computer
interaction and intelligent surveillance. However, view variations and noisy data bring …
interaction and intelligent surveillance. However, view variations and noisy data bring …
Skeleton-based action recognition using spatio-temporal LSTM network with trust gates
Skeleton-based human action recognition has attracted a lot of research attention during the
past few years. Recent works attempted to utilize recurrent neural networks to model the …
past few years. Recent works attempted to utilize recurrent neural networks to model the …
Augmented skeleton based contrastive action learning with momentum lstm for unsupervised action recognition
Action recognition via 3D skeleton data is an emerging important topic. Most existing
methods rely on hand-crafted descriptors to recognize actions, or perform supervised action …
methods rely on hand-crafted descriptors to recognize actions, or perform supervised action …