Reconstruction of parametrized model using only three vanishing points from a single image 


Vol. 29,  No. 3, pp. 419-425, Mar.  2004


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  Abstract

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera. Our approach is to only compute three vanishing points without informations such as the focal length and rotation matrix from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector v. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

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  Cite this article

[IEEE Style]

J. Choi and Y. Yoon, "Reconstruction of parametrized model using only three vanishing points from a single image," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 3, pp. 419-425, 2004. DOI: .

[ACM Style]

Jong-soo Choi and Yong-In Yoon. 2004. Reconstruction of parametrized model using only three vanishing points from a single image. The Journal of Korean Institute of Communications and Information Sciences, 29, 3, (2004), 419-425. DOI: .

[KICS Style]

Jong-soo Choi and Yong-In Yoon, "Reconstruction of parametrized model using only three vanishing points from a single image," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 3, pp. 419-425, 3. 2004.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880