Activity Recognition: Fundamentals and Applications

Activity recognition is an approach that makes use of a number of observations on the activities of one or more agents, as well as the conditions of their surrounding environment, with the end goal of identifying the actions and objectives of those individuals. Because of its ability to offer personalized support for a wide variety of applications and its connections to a wide variety of other fields of study, such as medicine, human-computer interaction, or sociology, this area of research has attracted the attention of several communities within the field of computer science since the 1980s.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Activity recognition

Chapter 2: Computer vision

Chapter 3: Artificial neural network

Chapter 4: Machine learning

Chapter 5: Gesture recognition

Chapter 6: Recurrent neural network

Chapter 7: Context awareness

Chapter 8: Transfer learning

Chapter 9: Convolutional neural network

Chapter 10: List of datasets for machine-learning research

(II) Answering the public top questions about activity recognition.

(III) Real world examples for the usage of activity recognition in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of activity recognition' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of activity recognition.