Reconstruction of linearly parameterized models three vanishing points from a single image of perspective projection

A method using only three vanishing points to recover the dimensions of object and its pose from a single image of perspective projection with a camera of unknown focal length is presented. Our approach is to compute the dimensions of objects which are represented by the unit vector of objects from the image. The dimension vector v for the 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. Therefore, experimental results show the evaluated values of the object dimensions from a single image using three vanishing points. In addition, the actual dimensions of object from the image agree well with the calculated results.