Feature-based 3D surface modeling by improved constrained triangular meshes

Triangular meshes are suitable representations for the large amounts of 3D data produced by range sensors. 3D object recognition tasks are complicated due to the high resolutions involved. We present a new technique to improve the interpretation quality of triangular meshes and to bridge the gap between raw sensory data and symbolic models used for recognition. We efficiently describe the surface features and avoid insignificant high resolution details. We accentuate the surface features by locally and incrementally improving the mesh topographic properties. The resulting locally-optimal triangular mesh removes the artifacts inevitably introduced by scene digitization. This simplifies subsequent object recognition tasks.