In recent years, human activity recognition has gained significant attention inside the scientific community. The enhanced spotlight is on the ground of its direct application in multiple domains. The latest research at the Department of Computer Science validates this assumption. Assistant Professor Dr V M Manikandan, and the 4th year B Tech Student Chaitanya Krishna Pasula have published a chapter titled An analysis of human activity recognition systems and their importance in the current era in the book Computational Intelligence Based Solutions for Vision Systems. The book is published by IOP Publishing Ltd.
Explanation of the chapter
Human activity recognition is one of the most interesting and active research areas in computer vision. More research efforts are being put towards automatically identifying and analysing human activities due to their emerging importance in everyday applications. It serves applications in various areas like security video surveillance, smart homes, healthcare, human-computer interaction, virtual reality, robotics, and digital entertainment. Numerous papers have been published in the domain of human activity recognition. This book chapter discusses the various applications of human activity recognition, different methods available for automatic activity detection from videos, and the advantages of the human activity recognition system. It also describes the challenges in designing and implementing human activity detection schemes. Researchers further explain the publicly available datasets used for training and evaluating the systems for human activity recognition. The efficiency parameters used to evaluate the human activity recognition systems are also briefed in this chapter. The chapter is concluded by comparing the methodologies and speculating the possibilities of future research in this field.
In the future, the researchers are planning to design and implement an activity recognition system to identify abnormal activities in public places for safety purposes. This book chapter will be a helpful reference for UG/PG/Ph.D students who aspire to research in the domain of activity detection from video.