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Content Provider | IEEE Xplore Digital Library |
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Author | Sungho Kim Inso Kweon Incheol Kim |
Copyright Year | 2003 |
Description | Author affiliation: Dept. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea (Sungho Kim; Inso Kweon) |
Abstract | We propose a vision based 3D object recognition and tracking system, which provides high level scene descriptions such as object identification and 3D pose information. The system is composed of object recognition part and real-time tracking part. In object recognition, we propose a feature which is robust to scale, rotation, illumination change and background clutter. A probabilistic voting scheme maximizes the conditional probability defined by the features in correspondence to recognize an object of interest. As a result of object recognition, we obtain the homography between the model image and the input scene. In tracking, a Lie group formalism is used to cast the motion computation problem into simple geometric terms so that tracking becomes a simple optimization problem. An initial object pose is estimated using correspondences between the model image and the 3D CAD model which are predefined and the homography which relates the model image to the input scene. Results from the experiments show the robustness of the proposed system. |
Sponsorship | IEEE Robotics & Autom. Soc. Nat. Sci. Council, Taiwan, Ministr. Educ., Taiwan |
Starting Page | 2123 |
Ending Page | 2128 |
File Size | 408171 |
Page Count | 6 |
File Format | |
ISBN | 0780377362 |
ISSN | 10504729 |
DOI | 10.1109/ROBOT.2003.1241907 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2003-09-14 |
Publisher Place | Taiwan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Robustness Object recognition Layout Lighting Tracking Service robots Indoor environments Data mining Computer science Real time systems |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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