Construction of 3D views from stereoscopic triplets of images

We present an approach to construct; 3D facets using trinocular stereovision and characterize them by a set of reliable attributes. A facet of a polyedric object is supposed to be projected on the image plane as a homogeneous region surrounded by a chain of 2D segments. These ordered chains, called 2D facets, are extracted from each image of a stereoscopic triplet using the cooperation between single contour map and a series of region maps. These maps are automatically generated according to a coarse-to-fine approach, in order to make the most contrasted regions appear first. The 3D facets are then reconstructed by a technique based on the cooperation of 2D information (2D facets and 2D segments) and 3D information (3D segments provided by a stereovision algorithm). The difficult point is the ordering of the 3D segments constituting the sides of a 3D facet, and is solved by an original algorithm which uses the ordering of three matched 2D facets. Each 3D facet is characterized by a set of intrinsic and extrinsic parameters in order to be efficiently used during the 3D reconstruction of the object to be modelled. As an example, we explain the estimation of the surface of a facet. The original contributions of this work are the cooperation between several heterogeneous data and the use of low quality images, which require robust algorithms