Efficient 3D Shape Acquisition and Registration Using Hybrid Scanning Data

We consider efficient 3D shape acquisition and surface registration using dissimilar laser range scanners. Most previous solutions do not use global shape information for optimal local surface registration. In this paper, we exploit the fundamental 3D scanning “trade-off ” between the cov-erage of the global shape structure and numerous local sur-face patches to construct a hybrid laser scanning system provided that it can acquire both global and local shape in-formation. The scanned low-resolution global shape data supplies the global shape structural prior for registering the high-resolution local 3D surface patches. Local sur-face patches can thus be optimally registered requiring less overlapping and thus reducing redundancy. To verify the feasibility of this system, we have implemented a prototype based on two laser range scanners, a hand-held one for the coarse global low-resolution model and a second station-ary high-resolution line scanning system. This prototype system was evaluated for various real 3D models. Based on geometric data alone without using texture information, the results show that the proposed hybrid 3D scanning ap-proach outperforms previous approaches in the presence of noise and outliers. The approach can be further applied to other practical 3D shape applications