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

Abstract

In this paper, we propose a new method using only three vanishing points to recover the dimensions of object and its pose from a single image with a camera of unknown focal length. Our approach is to compute the dimensions of objects represented by the unit vector of objects from an image. The dimension vector v 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 for the dimensions of object for a 3D model from matches to a single 2D image. Experimental results show the actual dimensions of object from an image agree well with the calculated results.