Computer Vision and Machine Learning with RGB-D Sensors (Advances in Computer Vision and Pattern Recognition) - Hardcover

Hardcover

ISBN 10: 3319086502 ISBN 13: 9783319086507

Publisher: Springer, 2014

Synopsis

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.

About this title

From the Back Cover

The combination of high-resolution visual and depth sensing, supported by machine learning, opens up new opportunities to solve real-world problems in computer vision.

This authoritative text/reference presents an interdisciplinary selection of important, cutting-edge research on RGB-D based computer vision. Divided into four sections, the book opens with a detailed survey of the field, followed by a focused examination of RGB-D based 3D reconstruction, mapping and synthesis. The work continues with a section devoted to novel techniques that employ depth data for object detection, segmentation and tracking, and concludes with examples of accurate human action interpretation aided by depth sensors.

Topics and 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 innovative 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

Researchers and practitioners working in computer vision, HCI and machine learning will find this to be a must-read text. The book also serves as a useful reference for graduate students studying computer vision, pattern recognition or multimedia.

About the Author

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.

Edition details

• Publisher: Springer
• Publication date: 2014
• ISBN 10: 3319086502
• ISBN 13: 9783319086507
• Binding: Hardcover
• Language: English
• Number of pages: 326
• Editor: Shao Ling, Han Jungong, Kohli Pushmeet, Zhang Zhengyou