Visible surface reconstruction with accurate localization of object boundaries

A common limitation of many techniques for 3-D reconstruction from multiple perspective views is the poor quality of the results near the object boundaries. The interpolation process applied to "unstructured" 3-D data ("clouds" of non-connected 3-D points) plays a crucial role in the global quality of the 3-D reconstruction. We present a method for interpolating unstructured 3-D data, which is able to perform a segmentation of such data into different data sets that correspond to different objects. The algorithm is also able to perform an accurate localization of the boundaries of the objects. The method is based on an iterative optimization algorithm. As a first step, a set of surfaces and boundary curves are generated for the various objects. Then, the edges of the original images are used for refining such boundaries as best as possible. Experimental results with real data are presented for proving the effectiveness of the proposed algorithm.