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ICRA
2003
IEEE

Robust model-based 3D object recognition by combining feature matching with tracking

9 years 19 days ago
Robust model-based 3D object recognition by combining feature matching with tracking
− 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 t...
Sungho Kim, In-So Kweon, Incheol Kim
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICRA
Authors Sungho Kim, In-So Kweon, Incheol Kim
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