Computer vision based UGV steering

• Autorzy: Simak V.
• Języki publikacji: EN

Abstrakty

EN

This report deals with a computer vision system for unmanned ground vehicle. The concentrated aspects include the comparison between image and model and intrinsic and extrinsing parameters of camera.

Słowa kluczowe

EN

unmanned ground vehicle; road tracking; comparison; model

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2007
• Tom: Vol. 3, no 2
• Strony: 87--101
• Opis fizyczny: Bibliogr. 12 poz., fig., tab.

Twórcy

autor

Simak V.

• University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering

Bibliografia

• [1] http://bmrc.berkeley.edu/frame/research/mpeg/mpeg_overview.html (Description of MPEG standard)
• [2] http://www.cplusplus.com/ (C++ code examples, commands overviews)
• [3] http://en.wikipedia.org/wiki/Covariance (Covariance mathematical formulas and features)
• [4] http://www.darpa.mil/grandchallenge/index.asp (Darpa - Grand challenge competition homepage)
• [5] http://www.cs.cf.ac.uk/Dave/Multimedia/node252.html (Motion vector description)
• [6] http://www.mathworks.com/ (Matlab code exchange website)
• [7] http://research.graphicon.ru/machine-learning/gml-ransac-matlab-toolbox-2.html (Ransac toolbox and example)
• [8] http://forums.nvidia.com/index.php?showtopic=28511 (information about NVidia GeForce graphics cards)
• [9] http://www.automobilemag.com/am/1998/land_rover/discovery/specifications.html (vehicle specification)
• [10] http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FISHER/RANSAC/ (RANSAC specification)
• [11] Distinctive Image Features from Scale-Invariant Keypoints DAVID G. LOWE Computer Science Department, University of British Columbia, Vancouver, B.C., Canada [e-mail] Received January 10, 2003; Revised January 7, 2004; Accepted January 22, 2004
• [12] IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 5, NO. 4, DECEMBER 2004 309 Color-Based Road Detection in Urban Traffic Scenes Yinghua He, Hong Wang, and Bo Zhang