Camarena, F.; Gonzalez-Mendoza, M.; Chang, L.; Cuevas-Ascencio, R. An Overview of the Vision-Based Human Action Recognition Field. Math. Comput. Appl.2023, 28, 61.
Camarena, F.; Gonzalez-Mendoza, M.; Chang, L.; Cuevas-Ascencio, R. An Overview of the Vision-Based Human Action Recognition Field. Math. Comput. Appl. 2023, 28, 61.
Camarena, F.; Gonzalez-Mendoza, M.; Chang, L.; Cuevas-Ascencio, R. An Overview of the Vision-Based Human Action Recognition Field. Math. Comput. Appl.2023, 28, 61.
Camarena, F.; Gonzalez-Mendoza, M.; Chang, L.; Cuevas-Ascencio, R. An Overview of the Vision-Based Human Action Recognition Field. Math. Comput. Appl. 2023, 28, 61.
Abstract
Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human-computer interaction. These applications often require one core task: video-based human action recognition. Research in human video-based human action recognition is vast and ongoing, making it difficult to assess the full scope of available methods and current trends. This survey provides an in-depth exploration of the vision-based human action recognition field, comprehensively offering the available techniques and their evolution, highlighting the cutting-edge ideas driving its development. We also analyze the most used keywords in research papers over the past years to identify trends and predict possible future directions. Hence, this concise survey helps researchers understand the breadth of existing approaches, evaluate current research trends, and stay up-to-date on potential developments.
Keywords
video-based human action recognition; Action Recognition; Deep Learning Methods; handcrafted Methods; Human Action; Overview
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
