抄録
Representing a real-world object in a computer vision system by using a range finder is one currently important subject. However, it is difficult to display a 3-D object at high speed with raw range data because of the scattered distribution and enormous quantities of the data. An efficient method for scattered range data re-sampling by uniform cube-based segmentation is proposed in this paper. By analyzing scattered range data delivered from optical measuring devices, the outline of a 3-D object is obtained, a group of cubes are then formed by making the cross sections in object space. Then, the scattered range data are divided into cubes. Based on re-sampling of the data inside each cube, lattice points in new patches are generated. By employing the proposed method, a 3-D object can be reconstructed automatically with fewer patches and displayed in the surroundings of 3-D vision at high speed.
