The three-dimensional (3-D) workflow (acquisition-processing-compression) is, in most cases, sequenced into several independent steps. Such approaches result in an acquisition of an important number of 3-D points. After acquisition, the first processing step is a simplification of the data by suppressing many of the computed points. We propose a coarse-to-fine acquisition system that makes it possible to obtain simplified data directly from the acquisition. By calculating some complementary information from two-dimensional (2-D) images, such as 3-D normals, multiple-homogeneous regions will be segmented and affected for a given primitive class. In contrast to other studies, the whole process is not based on a mesh. The obtained model is simplified directly from the 2-D data acquired by a 3-D scanner.