Advances in Computer Vision and Pattern Recognition

Consumer Depth Cameras for Computer Vision

Research Topics and Applications

Editors: Fossati, A., Gall, J., Grabner, H., Ren, X., Konolige, K. (Eds.)

  • Describes a topic of computer vision that will be key in coming years
  • With a broad appeal, bridging academic and corporate research
  • Provides publicly-available code for many of the applications described
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  • ISBN 978-1-4471-4640-7
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Hardcover $129.00
price for USA
  • ISBN 978-1-4471-4639-1
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About this book

The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications. This authoritative text reviews the scope and impact of this rapidly growing field, describing the most promising Kinect-based research activities, discussing significant current challenges, and showcasing exciting applications. Features: presents contributions from an international selection of preeminent authorities in their fields, from both academic and corporate research; addresses the classic problem of multi-view geometry of how to correlate images from different viewpoints to simultaneously estimate camera poses and world points; examines human pose estimation using video-rate depth images for gaming, motion capture, 3D human body scans, and hand pose recognition for sign language parsing; provides a review of approaches to various recognition problems, including category and instance learning of objects, and human activity recognition; with a Foreword by Dr. Jamie Shotton.

About the authors

Dr. Andrea Fossati and Dr. Helmut Grabner are post-doctoral researchers in the Computer Vision Laboratory at ETH Zurich, Switzerland.

Dr. Juergen Gall is a Senior Researcher at the Max Planck Institute for Intelligent Systems, Tübingen, Germany.

Dr. Xiaofeng Ren is a Research Scientist at the Intel Science and Technology Center for Pervasive Computing, Intel Labs, and an Affiliate Assistant Professor at the Department of Computer Science and Engineering of the University of Washington, Seattle, WA, USA.

Dr. Kurt Konolige is a Senior Researcher at Industrial Perception Inc., Palo Alto, CA, USA.

Reviews

From the reviews:

“Consumer Depth Cameras for Computer Vision is among the first few written from a research point of view. It is based on research published in the Workshop on Consumer Depth Cameras and includes some of the notable researchers in the field and the original team behind Kinect itself. It’s an excellent resource for researchers working in computer vision and robotic vision or for students having knowledge of vision who wish to start working with Kinect. … highly recommend this book to any researcher of Kinect.” (Owais Mehmood, IAPR Newsletter, Vol. 35 (3–2), July, 2013)

Table of contents (10 chapters)

  • 3D with Kinect

    Smisek, Jan (et al.)

    Pages 3-25

  • Real-Time RGB-D Mapping and 3-D Modeling on the GPU Using the Random Ball Cover

    Bauer, Sebastian (et al.)

    Pages 27-48

  • A Brute Force Approach to Depth Camera Odometry

    Israël, Jonathan (et al.)

    Pages 49-60

  • Key Developments in Human Pose Estimation for Kinect

    Kohli, Pushmeet (et al.)

    Pages 63-70

  • A Data-Driven Approach for Real-Time Full Body Pose Reconstruction from a Depth Camera

    Baak, Andreas (et al.)

    Pages 71-98

Buy this book

eBook $99.00
price for USA
  • ISBN 978-1-4471-4640-7
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $129.00
price for USA
  • ISBN 978-1-4471-4639-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Consumer Depth Cameras for Computer Vision
Book Subtitle
Research Topics and Applications
Editors
  • Andrea Fossati
  • Juergen Gall
  • Helmut Grabner
  • Xiaofeng Ren
  • Kurt Konolige
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2013
Publisher
Springer-Verlag London
Copyright Holder
Springer-Verlag London
eBook ISBN
978-1-4471-4640-7
DOI
10.1007/978-1-4471-4640-7
Hardcover ISBN
978-1-4471-4639-1
Series ISSN
2191-6586
Edition Number
1
Number of Pages
XVI, 210
Topics