Apress

Consumer Depth Cameras for Computer Vision

Research Topics and Applications

By Andrea Fossati , Juergen Gall , Helmut Grabner , Xiaofeng Ren , Kurt Konolige

Consumer Depth Cameras for Computer Vision Cover Image

This up-to-date and authoritative book surveys the most promising Kinect-based research activities, discussing current challenges to the adaptation of consumer depth cameras, and showcasing exciting applications that extend far beyond entertainment and gaming.

Full Description

  • ISBN13: 978-1-4471-4639-1
  • 228 Pages
  • User Level: Science
  • Publication Date: October 3, 2012
  • Available eBook Formats: PDF
  • eBook Price: $109.00
Buy eBook Buy Print Book Add to Wishlist

Related Titles

Full Description
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.
Table of Contents

Table of Contents

  1. Part I: 3D Registration and Reconstruction.
  2. 3D with Kinect.
  3. Real
  4. Time RGB
  5. D Mapping and 3
  6. D Modeling on the GPU using the Random Ball Cover.
  7. A Brute Force Approach to Depth Camera Odometry.
  8. Part II: Human Body Analysis.
  9. Key Developments in Human Pose Estimation for Kinect.
  10. A Data
  11. Driven Approach for Real
  12. Time Full Body Pose Reconstruction from a Depth Camera.
  13. Home 3D Body Scans from a Single Kinect.
  14. Real
  15. Time Hand Pose Estimation using Depth Sensors.
  16. Part III: RGB
  17. D Datasets.
  18. A Category
  19. Level 3D Object Dataset: Putting the Kinect to Work.
  20. RGB
  21. D Object Recognition: Features, Algorithms, and a Large Scale Benchmark.
  22. RGBD
  23. HuDaAct: A Color
  24. Depth Video Database for Human Daily Activity Recognition.
Errata

If you think that you've found an error in this book, please let us know about it. You will find any confirmed erratum below, so you can check if your concern has already been addressed.

* Required Fields

No errata are currently published