Computer Vision | Three-Dimensional Hand Tracking and Surface-Geometry Measurement for a Robot-Vision System

Chris Yu-Liang Liu

ISBN 10: 3838309413 / ISBN 13: 9783838309415

Published by LAP LAMBERT Academic Publishing, 2010

About this Item

Computer Vision | Three-Dimensional Hand Tracking and Surface-Geometry Measurement for a Robot-Vision System | Chris Yu-Liang Liu | Taschenbuch | 92 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838309415 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 101493680

Bibliographic Details

• Title: Computer Vision | Three-Dimensional Hand Tracking and Surface-Geometry Measurement for a Robot-Vision System
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2010
• Language: English
• ISBN 10: 3838309413
• ISBN 13: 9783838309415
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 155 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book describes the design, implementation, calibration and testing of two vision systems of a robot-vision system for a service robot to recognize objects and perform object-related tasks from task guidance and demonstration provided by a general user. First, real-time tracking of a human hand is achieved using images acquired from three calibrated synchronized cameras. Hand pose is determined from positions of physical markers and input to the robot system in real-time. Second, a multi-line laser camera range sensor is mounted on a robot end-effector to provide 3D geometry information about objects in the robot environment. The laser-camera sensor includes two cameras to provide stereo vision. For hand tracking, a novel score-based hand tracking scheme is presented employing dynamic multi-threshold marker detection, stereo camera-pair utilization scheme, marker matching and labeling using epipolar geometry and hand pose axis analysis, to enable real-time hand tracking under occlusion and non-uniform lighting environments. For surface-geometry measurement, two different approaches are analyzed for 2D to 3D coordinate mapping, using Bezier surface fitting and neural networks.

About the Author

Chris Y. Liu earned his MASc in Systems Design Engineering at University of Waterloo, BSc in Computer Science at Trent University, diploma in Computer Programming and System Analysis at Seneca College, and is now an IT Professional in Ontario.