A common limitation of many techniques for 3-D reconstruction from multiple
perspective views is the poor quality of the results near the object bound
aries, The interpolation process applied to "unstructured" 3-D data ("cloud
s" of non-connected 3-D points) plays a crucial role in the global quality
of the 3-D reconstruction. In this paper, me present a method for interpola
ting unstructured 3-D data, which is able to perform a segmentation of such
data into different data sets that correspond to different objects. The al
gorithm 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 t
he various objects, Then, the edges of the original images are used for ref
ining such boundaries as best as possible. Experimental results with real d
ata are presented for proving the effectiveness of the proposed algorithm.