Consumer depth cameras for computer vision : research topics and applications
Author(s)
Bibliographic Information
Consumer depth cameras for computer vision : research topics and applications
（Advances in computer vision and pattern recognition / Sameer Singh, Sing Bing Kang, series editors）
Springer, c2013
- hbk.
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Formerly CIP Uk
Includes bibliographical references and index
Description and Table of Contents
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
Part I: 3D Registration and Reconstruction
3D with Kinect
Jan Smisek, Michal Jancosek, and Tomas Pajdla
Real-Time RGB-D Mapping and 3-D Modeling on the GPU using the Random Ball Cover
Sebastian Bauer, Jakob Wasza, Felix Lugauer, Dominik Neumann, and Joachim Hornegger
A Brute Force Approach to Depth Camera Odometry
Jonathan Israel, and Aurelien Plyer
Part II: Human Body Analysis
Key Developments in Human Pose Estimation for Kinect
Pushmeet Kohli, and Jamie Shotton
A Data-Driven Approach for Real-Time Full Body Pose Reconstruction from a Depth Camera
Andreas Baak, Meinard Muller, Gaurav Bharaj, Hans-Peter Seidel, and Christian Theobalt
Home 3D Body Scans from a Single Kinect
Alexander Weiss, David Hirshberg, and Michael J. Black
Real-Time Hand Pose Estimation using Depth Sensors
Cem Keskin, Furkan Kirac, Yunus Emre Kara, and Lale Akarun
Part III: RGB-D Datasets
A Category-Level 3D Object Dataset: Putting the Kinect to Work
Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko, and Trevor Darrell
RGB-D Object Recognition: Features, Algorithms, and a Large Scale Benchmark
Kevin Lai, Liefeng Bo, Xiaofeng Ren, and Dieter Fox
RGBD-HuDaAct: A Color-Depth Video Database for Human Daily Activity Recognition
Bingbing Ni, Gang Wang, and Pierre Moulin
by "Nielsen BookData"
