Spatiotemporal human representation based on 3D visual perception data is a rapidly
growing research area. Representations can be broadly categorized into two groups …

The fields of human activity analysis have recently begun to diversify. Many researchers
have taken much interest in developing action recognition or action prediction methods. The …

In recent years, Human Activity Recognition (HAR) has become one of the most important
research topics in the domains of health and human-machine interaction. Many Artificial …

Graph convolutional networks have been widely used for skeleton-based action recognition
due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a …

Abstract 3D action recognition–analysis of human actions based on 3D skeleton data–
becomes popular recently due to its succinctness, robustness, and view-invariant …

Human action recognition based on skeletons has wide applications in human–computer
interaction and intelligent surveillance. However, view variations and noisy data bring …

Abstract Long Short-Term Memory (LSTM) networks have shown superior performance in
3D human action recognition due to their power in modeling the dynamics and …

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 …

Human action recognition in 3D skeleton sequences has attracted a lot of research attention.
Recently, long short-term memory (LSTM) networks have shown promising performance in …

Human actions can be represented by the trajectories of skeleton joints. Traditional methods
generally model the spatial structure and temporal dynamics of human skeleton with hand …