Consumer Depth Cameras for Computer Vision

Research Topics and Applications

  • Andrea Fossati
  • Juergen Gall
  • Helmut Grabner
  • Xiaofeng Ren
  • Kurt Konolige

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. 3D Registration and Reconstruction

    1. Front Matter
      Pages 1-2
    2. Jan Smisek, Michal Jancosek, Tomas Pajdla
      Pages 3-25
    3. Sebastian Bauer, Jakob Wasza, Felix Lugauer, Dominik Neumann, Joachim Hornegger
      Pages 27-48
    4. Jonathan Israël, Aurélien Plyer
      Pages 49-60
  3. Human Body Analysis

    1. Front Matter
      Pages 61-62
    2. Pushmeet Kohli, Jamie Shotton
      Pages 63-70
    3. Andreas Baak, Meinard Müller, Gaurav Bharaj, Hans-Peter Seidel, Christian Theobalt
      Pages 71-98
    4. Alexander Weiss, David Hirshberg, Michael J. Black
      Pages 99-117
    5. Cem Keskin, Furkan Kıraç, Yunus Emre Kara, Lale Akarun
      Pages 119-137
  4. RGB-D Datasets

    1. Front Matter
      Pages 139-139
    2. Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko et al.
      Pages 141-165
    3. Kevin Lai, Liefeng Bo, Xiaofeng Ren, Dieter Fox
      Pages 167-192
    4. Bingbing Ni, Gang Wang, Pierre Moulin
      Pages 193-208
  5. Back Matter
    Pages 209-210

About this book


The launch of Microsoft’s Kinect, the first high-resolution depth-sensing camera for the consumer market, generated considerable excitement not only among computer gamers, but also within the global community of computer vision researchers.

The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications such virtual fitting rooms, training for athletes, and assistance for the elderly. This authoritative text/reference 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.

Topics and 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 of Microsoft Research, Cambridge, UK

This broad-ranging overview is a must-read for researchers and graduate students of computer vision and robotics wishing to learn more about the state of the art of this increasingly “hot” topic.


3D Point Cloud Computer Vision Consumer Depth Cameras Kinect Pattern Recognition

Editors and affiliations

  • Andrea Fossati
    • 1
  • Juergen Gall
    • 2
  • Helmut Grabner
    • 3
  • Xiaofeng Ren
    • 4
  • Kurt Konolige
    • 5
  1. 1.Computer Vision LaboratoryETH ZürichZürichSwitzerland
  2. 2.Perceiving Systems DepartmentMax Planck Inst. for Intelligent SystemsTübingenGermany
  3. 3.Computer Vision LaboratoryETH ZürichZürichSwitzerland
  4. 4.Intel Science and Technology CenterSeattleUSA
  5. 5.Industrial PerceptionPalo AltoUSA

Bibliographic information