Computer Vision and Machine Learning with RGB-D Sensors
(Sprache: Englisch)
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...
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Klappentext zu „Computer Vision and Machine Learning with RGB-D Sensors “
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.
Inhaltsverzeichnis zu „Computer Vision and Machine Learning with RGB-D Sensors “
Part I: Surveys3D Depth Cameras in Vision: Benefits and Limitations of the Hardware Achuta Kadambi, Ayush Bhandari and Ramesh Raskar
A State-of-the-Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets Kai Berger
Part II: Reconstruction, Mapping and Synthesis
Calibration Between Depth and Color Sensors for Commodity Depth Cameras Cha Zhang and Zhengyou Zhang
Depth Map Denoising via CDT-Based Joint Bilateral Filter Andreas Koschan and Mongi Abidi
Human Performance Capture Using Multiple Handheld Kinects Yebin Liu, Genzhi Ye, Yangang Wang, Qionghai Dai and Christian Theobalt
Human Centered 3D Home Applications via Low-Cost RGBD Cameras Zhenbao Liu, Shuhui Bu and Junwei Han
Matching of 3D Objects Based on 3D Curves Christian Feinen, Joanna Czajkowska, Marcin Grzegorzek and Longin Jan Latecki
Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinects Kai Berger, Marc Kastner, Yannic Schroeder and Stefan Guthe
Part III: Detection, Segmentation and Tracking
RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons Yingli Tian
RGB-D Human Identification and Tracking in a Smart Environment Jungong Han and Junwei Han
Part IV: Learning-Based Recognition
Feature Descriptors for Depth-Based Hand Gesture Recognition Fabio Dominio, Giulio Marin, Mauro Piazza and Pietro Zanuttigh
Hand Parsing and Gesture Recognition with a Commodity Depth Camera Hui Liang and Junsong Yuan
Learning Fast Hand Pose Recognition Eyal Krupka, Alon Vinnikov, Ben Klein, Aharon Bar Hillel, Daniel Freedman, Simon Stachniak and Cem Keskin
Realtime Hand-Gesture Recognition Using RGB-D Sensor Yuan Yao, Fan Zhang and Yun Fu
Autoren-Porträt
Dr. Ling Shao is a Senior Lecturer (Associate Professor) in the Department of Electronic and Electrical Engineering at the University of Sheffield, UK. His publications include the Springer title Multimedia Interaction and Intelligent User Interfaces.Dr. Jungong Han is a Senior Scientist at Civolution Technology, Eindhoven, and a Guest Researcher at the Eindhoven University of Technology, Netherlands.
Dr. Pushmeet Kohli is a Senior Researcher in the Machine Learning and Perception Group at Microsoft Research Cambridge and an Associate in the Psychometrics Centre at the University of Cambridge, UK.
Dr. Zhengyou Zhang, IEEE Fellow and ACM Fellow, is a Principal Researcher and Research Manager of the Multimedia, Interaction, and Communication Group at Microsoft Research Redmond, WA, USA.
Bibliographische Angaben
- 2014, 2014, X, 316 Seiten, 148 farbige Abbildungen, Masse: 16 x 24,1 cm, Gebunden, Englisch
- Herausgegeben: Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang
- Verlag: Springer, Berlin
- ISBN-10: 3319086502
- ISBN-13: 9783319086507
- Erscheinungsdatum: 31.08.2014
Sprache:
Englisch
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