A focal cue for metric measurement of 3D surfaces

This paper finds a method for computing the best-focused location from an image and using it as a dimensional cue for acquisition of a 3D scene surface. In some situations in 3D vision, an object cannot be reconstructed into a 3D model with metric dimensions. Rather, it can only be reconstructed into a 3D structure up to a similarity transformation. To upgrade the 3D model from a similarity transformation to a Euclidean transformation, we propose a method based on the best-focused locations. By analyzing the blur distribution in an image, this method finds the best-focused locations from an image, which provides an additional cue for upgrading the reconstructed 3D structure. Hence, we can obtain not only the object's shape, but also the dimensions and sizes of surface features.