Consumer Depth Cameras For Computer Vision
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Consumer Depth Cameras for Computer Vision
Author: Andrea Fossati
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-10-03
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.
Computer Vision and Machine Learning with RGB-D Sensors
This book presents an interdisciplinary selection of cutting-edge research on RGB-D based computer vision. Features: discusses the calibration of color and depth cameras, the reduction of noise on depth maps and methods for capturing human performance in 3D; reviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption and obtain accurate action classification; presents an approach for 3D object retrieval and for the reconstruction of gas flow from multiple Kinect cameras; describes an RGB-D computer vision system designed to assist the visually impaired and another for smart-environment sensing to assist elderly and disabled people; examines the effective features that characterize static hand poses and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition and a novel hand segmentation and gesture recognition system.
Time-of-Flight and Structured Light Depth Cameras
This book provides a comprehensive overview of the key technologies and applications related to new cameras that have brought 3D data acquisition to the mass market. It covers both the theoretical principles behind the acquisition devices and the practical implementation aspects of the computer vision algorithms needed for the various applications. Real data examples are used in order to show the performances of the various algorithms. The performance and limitations of the depth camera technology are explored, along with an extensive review of the most effective methods for addressing challenges in common applications. Applications covered in specific detail include scene segmentation, 3D scene reconstruction, human pose estimation and tracking and gesture recognition. This book offers students, practitioners and researchers the tools necessary to explore the potential uses of depth data in light of the expanding number of devices available for sale. It explores the impact of these devices on the rapidly growing field of depth-based computer vision.