Computer Vision and Machine Learning with RGB-D Sensors

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 compute...

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Bibliographic Details
Other Authors: Shao, Ling (Editor)
Han, Jungong (Editor)
Kohli, Pushmeet (Editor)
Zhang, Zhengyou (Editor)
Corporate Author: SpringerLink (online služba) (Distributor) 
Format: eBook
Language:English
Published: Cham : Springer International Publishing : 2014
Series:Advances in Computer Vision and Pattern Recognition,
Genre/form:elektronické knihy
ISBN:9783319086514
Online Access:Plný text
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Table of 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