Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …

Recognizing the unseen combinations of action and different objects, namely (zero-shot)
compositional action recognition, is extremely challenging for conventional action …

Human behaviour analysis, human–computer interaction, and pervasive computing are
three areas where human activity recognition has recently attracted a lot of attention. Recent …

Graph convolutional networks (GCN) have attracted increasing interest in action recognition
in recent years. GCN models human skeleton sequences as spatio-temporal graphs. Also …

Abstract Skeleton-based Human Activity Recognition has recently sparked a lot of attention
because skeleton data has proven resistant to changes in lighting, body sizes, dynamic …

Intelligent video surveillance systems have been used recently for automatic monitoring of
human interactions. Although they play a significant role in reducing security concerns, there …

The recognition of human actions in videos is one of the most active research fields in
computer vision. The canonical approach consists in a more or less complex preprocessing …

Recently, human activity recognition using skeleton data is increasing due to its ease of
acquisition and finer shape details. Still, it suffers from a wide range of intra-class variation …

Prediction of human physical activities has become a necessity for some applications that
come with the development of wearable and portable hardware such as smartwatches and …

The aim of the algorithm is to detect the abnormal actions that are more prone to elderly
people in order to make them more independent and improve their quality of life. The …