Logo - springer
Slogan - springer

Computer Science - Image Processing | Human Action Recognition with Depth Cameras

Human Action Recognition with Depth Cameras

Wang, Jiang, Liu, Zicheng, Wu, Ying

2014, VIII, 59 p. 32 illus., 9 illus. in color.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$39.99

(net) price for USA

ISBN 978-3-319-04561-0

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase


learn more about Springer eBooks

add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$54.99

(net) price for USA

ISBN 978-3-319-04560-3

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • 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

Action recognition is an enabling technology for many real world applications, such as human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. In the past decade, it has attracted a great amount of interest in the research community. Recently, the commoditization of depth sensors has generated much excitement in action recognition from depth sensors. New depth sensor technology has enabled many applications that were not feasible before. On one hand, action recognition becomes far easier with depth sensors. On the other hand, the drive to recognize more complex actions presents new challenges.

One crucial aspect of action recognition is to extract discriminative features. The depth maps have completely different characteristics from the RGB images. Directly applying features designed for RGB images does not work.

Complex actions usually involve complicated temporal structures, human-object interactions, and person-person contacts. New machine learning algorithms need to be developed to learn these complex structures.

This work enables the reader to quickly familiarize themselves with the latest research in depth-sensor based action recognition, and to gain a deeper understanding of recently developed techniques. It will be of great use for both researchers and practitioners who are interested in human action recognition with depth sensors.

The 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 in action recognition from depth data, 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.

Content Level » Research

Keywords » 3D Action Recognition - 3D Sensors - Actionlet Ensemble - Depth Cameras - Human Action/Activity Recognition - Human Pose/Gesture Recognition - Human–Computer Interaction

Related subjects » HCI - Image Processing

Table of contents / Preface / Sample pages 

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Image Processing and Computer Vision.