Computer Vision and Machine Learning with RGB-D Sensors

Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang

Research output: Book/ReportBookpeer-review


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.
Original languageEnglish
Place of PublicationLondon
Number of pages328
ISBN (Print)9783319086507
Publication statusPublished - Aug 2014

Publication series

NameAdvances in Computer Vision and Pattern Recognition
ISSN (Electronic)2191-6586


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