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Human Activity Recognition and Prediction

  • Yun Fu

Table of contents

  1. Front Matter
    Pages i-vii
  2. Yu Kong, Yun Fu
    Pages 1-22
  3. Yu Kong, Yun Fu
    Pages 23-48
  4. Chengcheng Jia, Yun Fu
    Pages 49-69
  5. Chengcheng Jia, Wei Pang, Yun Fu
    Pages 71-85
  6. Chengcheng Jia, Yu Kong, Zhengming Ding, Yun Fu
    Pages 87-106
  7. Yu Kong, Yun Fu
    Pages 107-122
  8. Kang Li, Yun Fu
    Pages 123-151
  9. Kang Li, Sheng Li, Yun Fu
    Pages 153-174

About this book

Introduction

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. 

Keywords

Action Prediction Action Recognition Actionlets Activity Prediction Activity Recognition Computer Vision Discriminative Model Human Interaction Machine Learning Pattern Recognition RGB-D Transfer Learning

Editors and affiliations

  • Yun Fu
    • 1
  1. 1.Northeastern UniversityBostonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-27004-3
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-27002-9
  • Online ISBN 978-3-319-27004-3
  • Buy this book on publisher's site
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