Diving deep into human action recognition in aerial videos: A survey

Abstract

Human Action Recognition from Unmanned Aerial Vehicles is a dynamic research domain with significant benefits in scale, mobility, deployment, and covert observation. This paper offers a comprehensive review of state-of-the-art algorithms for human action recognition and provides a novel taxonomy that categorizes the reviewed methods into two broad categories: Localization based and Globalization based. These categories are defined by how actions are segmented from visual data and how their spatial and temporal structures are modeled. We examine these techniques, highlighting their strengths and limitations, and provide essential background on human action recognition, including fundamental concepts and challenges in aerial videos. Additionally, we discuss existing datasets, enabling a comparative analysis. This survey identifies gaps and suggests future research directions, serving as a catalyst for advancing human action recognition in aerial videos. To our knowledge, this is the first detailed review of this kind.