Intelligent Video Analytics for Human Action Recognition: The State of Knowledge

Abstract

The paper presents a comprehensive overview of intelligent video analytics and human action recognition methods. The article provides an overview of the current state of knowledge in the field of human activity recognition, including various techniques such as pose-based, tracking-based, spatio-temporal, and deep learning-based approaches, including visual transformers. We also discuss the challenges and limitations of these techniques and the potential of modern edge AI architectures to enable real-time human action recognition in resource-constrained environments.

Keywords

• intelligent video analytics
• edge AI
• visual transformers
• human activity recognition
• video surveillance
• pose-based HAR