Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Continuous growth in software, hardware and internet technology has enabled the growth of
internet-based sensor tools that provide physical world observations and data …

Human skeleton, as a compact representation of human action, has received increasing
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …

In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …

Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …

Group activity recognition is a crucial yet challenging problem, whose core lies in fully
exploring spatial-temporal interactions among individuals and generating reasonable group …

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

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 …

Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …