Consumer depth cameras for computer vision : research topics and applications

著者

    • Fossati, Andrea

書誌事項

Consumer depth cameras for computer vision : research topics and applications

edited by Andrea Fossati ... [et al.]

（Advances in computer vision and pattern recognition / Sameer Singh, Sing Bing Kang, series editors）

Springer, c2013

  • hbk.

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注記

Formerly CIP Uk

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

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

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