Recognizing human actions from unconstrained videos turns to be a major challenging task
in computer visualization approaches due to decreased accuracy in the feature classification …

In the domain of human action recognition, existing works mainly focus on using RGB,
depth, skeleton and infrared data for analysis. While these methods have the benefit of …

Automated human action recognition plays a critical role in the development of human-
machine communication, by aiming for a more natural interaction between artificial …

This work presents a novel approach to the problem of real-time human action recognition in
intelligent video surveillance. For more efficient and precise labeling of an action, this work …

Abstract Human Action Recognition (HAR) has achieved a remarkable milestone in the field
of computer vision. Apart from its varied applications in human–computer interactions …

The goal of human action recognition is to identify and understand the actions of people in
videos and export corresponding tags. In addition to spatial correlation existing in 2D …

Advancements in deep neural networks have contributed to near-perfect results for many
computer vision problems, such as object recognition, face recognition, and pose estimation …

Key-point trajectory based approaches to recognizing human actions in realistic videos have
recently shown promising results. However, their coverage of the entire actor is not sufficient …

Much research on human action recognition has been oriented toward the performance gain
on lab-collected datasets. Yet real-world videos are more diverse, with more complicated …