Advancements in Video-Based Human Activity Recognition: A Comprehensive Review of Methods, Challenges, and Applications

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Sabouri Mohammad

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Journal Paper

Paper Information

Journal: NEW RESEARCHES IN THE SMART CITY Year:2024 | Volume:3 | Issue:4 Page(s): 62-70

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Information Journal Paper

Title

Advancements in Video-Based Human Activity Recognition: A Comprehensive Review of Methods, Challenges, and Applications

Author(s)

Sabouri Mohammad | Issue Writer Certificate

Keywords

video colorization

deep learning diffusion models

evaluation metrics

Abstract

Human Activity Recognition (HAR) using video data has emerged as a pivotal research domain due to its transformative potential in areas such as surveillance, healthcare monitoring, and humancomputer interaction. This technology aims to automatically recognize and classify human behaviors and movements from sequences of images or videos by utilizing computer vision and machine learning techniques. However, challenges such as the diversity of human movements, lighting conditions, camera angles, frame rates, image quality and the need for real-time processing have complicated the development of effective systems in this field. This review provides a detailed examination of current HAR methodologies, highlighting both unimodal and multimodal approaches, and assessing their strengths and limitations. Particular emphasis is placed on real-time processing, which is critical for practical deployment in dynamic environments. Furthermore, this study explores a diverse set of real-world applications, discusses prevailing challenges-such as occlusions, noisy data, and computational constraints—and proposes considerations for future development. By addressing key obstacles and mapping out current trends, this paper aims to guide researchers and practitioners toward more robust, adaptive, and scalable HAR solutions.

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