Computer Vision and Machine Learning with RGB-D Sensors

Shao, Ling, Han, Jungong, Kohli, Pushmeet and Zhang, Zhengyou (2014) Computer Vision and Machine Learning with RGB-D Sensors. Advances in Computer Vision and Pattern Recognition . Springer, London. ISBN 9783319086507

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Official URL: http://dx.doi.org/10.1007/978-3-319-08651-4

Abstract

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.

Item Type: Book
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:
Depositing User: Paul Burns
Date Deposited: 10 Jun 2015 08:26
Last Modified: 25 Jan 2017 09:45
URI: http://nrl.northumbria.ac.uk/id/eprint/22795

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