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.
Author(s): Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang (eds.)
Series: Advances in Computer Vision and Pattern Recognition
Edition: 1
Publisher: Springer International Publishing
Year: 2014
Language: English
Pages: 316
Tags: Image Processing and Computer Vision; Artificial Intelligence (incl. Robotics); User Interfaces and Human Computer Interaction
Front Matter....Pages i-x
Front Matter....Pages 1-1
3D Depth Cameras in Vision: Benefits and Limitations of the Hardware....Pages 3-26
A State of the Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets....Pages 27-44
Front Matter....Pages 45-45
Calibration Between Depth and Color Sensors for Commodity Depth Cameras....Pages 47-64
Depth Map Denoising via CDT-Based Joint Bilateral Filter....Pages 65-89
Human Performance Capture Using Multiple Handheld Kinects....Pages 91-108
Human-Centered 3D Home Applications via Low-Cost RGBD Cameras....Pages 109-135
Matching of 3D Objects Based on 3D Curves....Pages 137-155
Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinect....Pages 157-169
Front Matter....Pages 171-171
RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons....Pages 173-194
RGB-D Human Identification and Tracking in a Smart Environment....Pages 195-211
Front Matter....Pages 213-213
Feature Descriptors for Depth-Based Hand Gesture Recognition....Pages 215-237
Hand Parsing and Gesture Recognition with a Commodity Depth Camera....Pages 239-265
Learning Fast Hand Pose Recognition....Pages 267-287
Real-Time Hand Gesture Recognition Using RGB-D Sensor....Pages 289-313
Back Matter....Pages 315-316
