Computer Vision and Machine Learning with RGB-D Sensors
Ling Shao (Hrsg.), Jungong Han (Hrsg.), Zhengyou Zhang (Hrsg.), Pushmeet Kohli (Hrsg.)
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Springer International Publishing
Naturwissenschaften, Medizin, Informatik, Technik / Anwendungs-Software
Beschreibung
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.
Kundenbewertungen
Consumer Electronics, Intelligent Systems, Computer Vision, Machine Learning, Human-Computer Interaction, Pattern Recognition, RGB-D Sensors