Computational Intelligence for Human Action Recognition

Human Action Recognition is a challenging area of research with increasing involvement of Computational Intelligence. The primary drive is to equip computing systems with the ability to recognize and interpret human activities from posture, pose, gesture, and facial expression. This systematic overview covers state-of-the-art techniques, intelligent techniques, and automation techniques. Recent research results and future advancements are discussed, making it useful for students, researchers, and senior researchers.

Format: Paperback / softback
Length: 126 pages
Publication date: 15 March 2022
Publisher: Taylor & Francis Ltd

Human Action Recognition is a complex and demanding field that is receiving significant attention from researchers worldwide. The substantial amount of research dedicated to this area is a clear indication of its importance. As Computational Intelligence continues to play a more significant role in our daily lives, the need for human activity recognition has become increasingly apparent within the research community. The primary objective of this endeavor is to develop computing systems capable of accurately recognizing and interpreting human activities, including posture, pose, gesture, and facial expression.

Human Activity Recognition is a fundamental component of cognitive science, and researchers are actively engaged in exploring its various aspects. This field encompasses a comprehensive overview of state-of-the-art computational intelligence techniques used for human action recognition. It emphasizes the use of diverse intelligent techniques to identify and classify different human actions. Additionally, it discusses the automation of human action recognition, which involves using machine learning algorithms and deep learning models to analyze and interpret human behavior.

Recent research results in this field have been groundbreaking, providing valuable insights into the potential of human activity recognition. These results have opened up new avenues for further advancements and have the potential to revolutionize various applications, such as healthcare, surveillance, and human-computer interaction.

In order to address the concerns of the relevant research community, the editors have compiled a comprehensive treatise that reflects the latest findings and advancements in human activity recognition. This treatise is designed to be useful to a wide readership, including students at undergraduate and postgraduate levels, researchers, and aspiring professionals. It provides a thorough understanding of the field, covering topics such as feature extraction, classification algorithms, and automation techniques.

The editors believe that this treatise will contribute to the growth and development of human activity recognition and will serve as a valuable resource for researchers, practitioners, and industry professionals alike. It is anticipated that this work will inspire new research initiatives and foster collaborations between different disciplines, ultimately leading to the advancement of this field and the betterment of human lives.

Dimension: 234 x 156 (mm)
ISBN-13: 9780367539436