Reconstruction of linearly parameterized models from a single image using the vanishing points

Authors:
Yong-In Yoon;Jang-Whan Im;Dae-Hyun Kim;Jong-Soo Choi;Jeong-Su Oh
Affiliations:
Department of Image Engineering Graduate School of Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul, South Korea;Department of Image Engineering Graduate School of Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul, South Korea;Department of Image Engineering Graduate School of Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul, South Korea;Department of Image Engineering Graduate School of Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul, South Korea;Department of Image Engineering, Pukyong National University, Pusan, South Korea
Venue:
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Year:
2003

Citing 4
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Abstract

We present a method using only three vanishing points to recover the dimensions of object and its pose from single image of perspective projection with a camera of unknown focal length. Our approach is to compute the dimensions of objects represented by the unit vector of objects from the image. The dimension vector v of objects can be solved by the standard nonlinear optimization techniques with a multistart method which generates multiple starting points for the optimizer by sampling the parameter space uniformly. This method allows model-based vision to be computed the dimensions of object for a 3D model from matches to a single 2D image. Experimental results demonstrate the dimension vector v of the proposed method from a single image using three vanishing points and show a performance of the proposed method compared to the conventional. Then, the actual dimensions of object from the image agree well with the calculated results.