Human Activity Recognition and Prediction
Human Activity Recognition and Prediction
Springer | Signals & Communication | January 20, 2016 | ISBN-10: 3319270028 | 174 pages | pdf | 5.6 mb
Springer | Signals & Communication | January 20, 2016 | ISBN-10: 3319270028 | 174 pages | pdf | 5.6 mb
by Yun Fu (Editor)
Covers the most state-of-the-art topics of activity recognition and prediction
Discusses both methodology and real-world practice of human activity recognition
Contains contributions from top experts in the field, who voice their unique perspectives included throughout
This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.
Number of Illustrations and Tables
64 illus., 6 in colour
Topics
Signal, Image and Speech Processing
Image Processing and Computer Vision
Biometrics
More info and Hardcover at Springer
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