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: deep learning-based HAR; edge AI; human activity recognition; intelligent video analytics; pose-based HAR; spatio-temporal-based HAR; tracking-based HAR; video surveillance; visual transformers.