Verkauf durch Sack Fachmedien

Shao / Zhang / Han

Computer Vision and Machine Learning with RGB-D Sensors

Medium: Buch
ISBN: 978-3-319-38105-3
Verlag: Springer International Publishing
Erscheinungstermin: 17.09.2016
Lieferfrist: bis zu 10 Tage

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.


Produkteigenschaften


  • Artikelnummer: 9783319381053
  • Medium: Buch
  • ISBN: 978-3-319-38105-3
  • Verlag: Springer International Publishing
  • Erscheinungstermin: 17.09.2016
  • Sprache(n): Englisch
  • Auflage: Softcover Nachdruck of the original 1. Auflage 2014
  • Serie: Advances in Computer Vision and Pattern Recognition
  • Produktform: Kartoniert, Previously published in hardcover
  • Gewicht: 5575 g
  • Seiten: 316
  • Format (B x H x T): 155 x 235 x 17 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

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.