A review of video-based human activity recognition: theory, methods and applications

Video-based human activity recognition (HAR) is an important task in many fields, such as healthcare monitoring, video surveillance, and sports analysis. This review paper aims to give an in-depth look at the current state of the art in HAR from 2018 to 2024. This will include a discussion of the different methods and models used for extracting, representing, and classifying human actions from video, as well as the challenges and limits of this field. The paper will also discuss recent improvements and plans for making HAR systems more accurate and useful. Even though there has been a lot of progress, a few knowledge gaps still need to be filled to make recognition more accurate and efficient. The purpose of this review paper is to offer scholars and professionals an overview of the theory, methods, and applications of HAR in videos. Through a critical analysis of the extant literature, this paper seeks to identify prospective avenues for future research and contribute towards advancing HAR systems that are more precise and efficient. By showing the different ways that HAR can be used, the paper shows how important this field is in many different areas.