Advances in Human Action Recognition: A Survey

TL;DR

This survey reviews recent advances in human action recognition, highlighting progress in recognizing low-level actions and high-level activities, and provides a comprehensive overview for guiding future research in computer vision applications.

Contribution

It offers a structured taxonomy of recent developments in human action recognition, serving as a valuable resource for researchers to understand current trends and identify future directions.

Findings

Comprehensive overview of recent methods in human action recognition

Identification of key challenges and research gaps

Framework for future research directions

Abstract

Human action recognition has been an important topic in computer vision due to its many applications such as video surveillance, human machine interaction and video retrieval. One core problem behind these applications is automatically recognizing low-level actions and high-level activities of interest. The former is usually the basis for the latter. This survey gives an overview of the most recent advances in human action recognition during the past several years, following a well-formed taxonomy proposed by a previous survey. From this state-of-the-art survey, researchers can view a panorama of progress in this area for future research.