Volume intersection with imprecise camera parameters

Abstract

Volume intersection is one of the simplest techniques for reconstructing 3D shapes from 2D silhouettes. 3D shapes can be reconstructed from multiple view images by back-projecting them from the corresponding viewpoints and intersecting the resulting solid cones. The camera position and orientation (extrinsic camera parameters) of each viewpoint with respect to the object are needed to accomplish reconstruction. However, even a little variation in the camera parameters makes the reconstructed 3D shape smaller than that with the exact parameters. The problem of optimizing camera parameters dealt with in this paper is determining good approximations from multiple silhouette images and imprecise camera parameters. This paper examines attempts to optimize camera parameters by reconstructing a 3D shape via the method of volume intersection. Reprojecting the reconstructed 3D shape to image planes, the camera parameters are determined by finding the projected silhouette images that result in minimal loss of area when compared to the original silhouette images. For relatively large displacement of camera parameters we propose a method repeating the optimization using dilated silhouettes which gradually shrink to original ones. Results of experiment show the effect of it.