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Vision-Based Human Activity Recognition: SpringerBriefs in Intelligent Systems

Kenzaburō Ōe

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Published in Vision Based Human Activity Recognition (SpringerBriefs In Intelligent Systems)

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Computer vision, a rapidly developing field of artificial intelligence, has significantly contributed to the advancement of human activity recognition (HAR) systems. Computer vision algorithms can extract meaningful information from images and videos, making them a powerful tool for recognizing and analyzing human activities in various scenarios, including healthcare, surveillance, and entertainment.

Vision-Based Human Activity Recognition (SpringerBriefs in Intelligent Systems)

by Yassine Maleh

4.5 out of 5

Language	:	English
File size	:	19727 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	229 pages

Vision-Based Human Activity Recognition: SpringerBriefs in Intelligent Systems provides a comprehensive overview of the state-of-the-art in vision-based HAR. This book explores the fundamental principles, algorithms, and applications of computer vision techniques for HAR. It covers a wide range of topics, including image and video processing, feature extraction, machine learning, and deep learning for HAR.

Key Features

In-depth coverage of the latest computer vision techniques for HAR, including image and video processing, feature extraction, machine learning, and deep learning.
Practical examples and case studies demonstrate the application of vision-based HAR systems in various real-world scenarios.
Comprehensive analysis of the strengths and limitations of different approaches helps readers understand the trade-offs involved in designing and implementing HAR systems.
Future research directions provide insights into the emerging trends in vision-based HAR.

Target Audience

Vision-Based Human Activity Recognition: SpringerBriefs in Intelligent Systems is an essential resource for researchers and practitioners in the field of HAR. It is also valuable for graduate students and advanced undergraduate students interested in learning about the latest advances in computer vision and HAR.

Image and Video Processing for HAR
Feature Extraction for HAR
Machine Learning for HAR
Deep Learning for HAR
Applications of Vision-Based HAR
Future Research Directions

Vision-Based Human Activity Recognition: SpringerBriefs in Intelligent Systems is a valuable resource for researchers and practitioners in the field of HAR. It provides a comprehensive overview of the state-of-the-art in vision-based HAR, covering the fundamental principles, algorithms, and applications of computer vision techniques for HAR.

This book is a valuable resource for anyone interested in learning more about vision-based HAR. It is well-written and easy to understand, making it an excellent choice for both researchers and practitioners.

Vision-Based Human Activity Recognition (SpringerBriefs in Intelligent Systems)

by Yassine Maleh

4.5 out of 5