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A real-time analysis of 3D scene from monocular images by observing known background

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3 Author(s)
K. Kondo ; Div. of Comput. Eng., Hyogo Univ., Japan ; S. Kobashi ; Y. Hata

In this paper, we propose a real-time method for analyzing 3-dimensional (3D) scene of objects from time series of monocular images. A single camera observes some points on the object so that 3D position of the points can be estimated by extended Kalman filter. We apply this method to two real-time applications. One is to acquire 3D geometry of an object, and another is to estimate 3D pose/position of an object. This approach needs no model data of the object a priori and achieves the estimation of 3D geometry and pose/position. In the experiments using a manipulation robot, we show that it is effective method to estimate 3D information with high accuracy.

Published in:

2005 International Symposium on Intelligent Signal Processing and Communication Systems

Date of Conference:

13-16 Dec. 2005