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Human Action Recognition with Depth Cameras

  • Book
  • © 2014

Overview

Authors:
  1. Jiang Wang

    1. Northwestern University, Evanston, USA

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  2. Zicheng Liu

    1. Microsoft Research, Redmond, USA

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  3. Ying Wu

    1. Northwestern University, Evanston, USA

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  • Presents a comprehensive overview of the state of the art in feature representation and machine learning algorithms for action recognition from depth sensors
  • Provides in-depth descriptions of novel feature representations and machine learning techniques
  • Covers lower-level depth and skeleton features, higher-level representations to model temporal structure and human-object interactions, and feature selection techniques for occlusion handling
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)

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Table of contents (4 chapters)

  1. Front Matter

    Pages i-viii
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  2. Introduction

    • Jiang Wang, Zicheng Liu, Ying Wu
    Pages 1-9

  3. Learning Actionlet Ensemble for 3D Human Action Recognition

    • Jiang Wang, Zicheng Liu, Ying Wu
    Pages 11-40

  4. Random Occupancy Patterns

    • Jiang Wang, Zicheng Liu, Ying Wu
    Pages 41-55

  5. Conclusion

    • Jiang Wang, Zicheng Liu, Ying Wu
    Pages 57-58

  6. Back Matter

    Pages 59-59
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Keywords

About this book

Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, including lower-level depth and skeleton features, higher-level representations to model the temporal structure and human-object interactions, and feature selection techniques for occlusion handling. This work enables the reader to quickly familiarize themselves with the latest research, and to gain a deeper understanding of recently developed techniques. It will be of great use for both researchers andpractitioners.

Reviews

“It is a relatively short but self-contained volume that presents recent advances in the popular research area of human action recognition. … I was quite pleased when the student, to whom I passed the book for a through read, told me at the end that he found it very useful and a good start for his research. ... book is a good read for someone with an existing background in depth camera technology and research about human action recognition.” (Nicola Bellotto, IAPR Newsletter, Vol. 37 (2), 2015)

Authors and Affiliations

  • Northwestern University, Evanston, USA

    Jiang Wang, Ying Wu

  • Microsoft Research, Redmond, USA

    Zicheng Liu

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