Human Activity Recognition and Prediction

✍ Scribed by Yun Fu

• Publisher: Springer
• Year: 2016
• Tongue: English
• Leaves: 179
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-vii
Introduction....Pages 1-22
Action Recognition and Human Interaction....Pages 23-48
Subspace Learning for Action Recognition....Pages 49-69
Multimodal Action Recognition....Pages 71-85
RGB-D Action Recognition....Pages 87-106
Activity Prediction....Pages 107-122
Actionlets and Activity Prediction....Pages 123-151
Time Series Modeling for Activity Prediction....Pages 153-174

✦ Subjects

Signal, Image and Speech Processing; Image Processing and Computer Vision; Biometrics