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Computer vision and machine learning with RGB-D sensors

Author: Jungong Han; Ling Shao, Dr.; Pushmeet Kohli; Zhengyou Zhang
Publisher: Cham : Springer, [2014] ©2014
Series: Advances in computer vision and pattern recognition
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Jungong Han; Ling Shao, Dr.; Pushmeet Kohli; Zhengyou Zhang
ISBN: 9783319086514 3319086510
OCLC Number: 884963948
Language Note: English.
Description: 1 online resource (x, 316 pages) : illustrations.
Contents: Part I: Surveys --
3D Depth Cameras in Vision: Benefits and Limitations of the Hardware --
A State-of-the-Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets --
Part II: Reconstruction, Mapping and Synthesis --
Calibration Between Depth and Color Sensors for Commodity Depth Cameras --
Depth Map Denoising via CDT-Based Joint Bilateral Filter --
Human Performance Capture Using Multiple Handheld Kinects --
Human Centered 3D Home Applications via Low-Cost RGBD Cameras --
Matching of 3D Objects Based on 3D Curves --
Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinects --
Part III: Detection, Segmentation and Tracking --
RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons --
RGB-D Human Identification and Tracking in a Smart Environment --
Part IV: Learning-Based Recognition --
Feature Descriptors for Depth-Based Hand Gesture Recognition --
Hand Parsing and Gesture Recognition with a Commodity Depth Camera --
Learning Fast Hand Pose Recognition --
Real time Hand-Gesture Recognition Using RGB-D Sensor.
Series Title: Advances in computer vision and pattern recognition
Responsibility: Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang, editors.

Abstract:

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  Read more...

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