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.One notable example of a consumer-grade sensor based on time-of-flight principle is Microsoft Kinect for Xbox One (2013). In principle, we must mention that the time-of-flight principle is not a new technology. It has been used for decades inanbsp;...
|Title||:||Computer Vision and Machine Learning with RGB-D Sensors|
|Author||:||Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang|
|Publisher||:||Springer - 2014-07-14|