Scaling registration of multiview range scans via motion averaging

Three-dimensional modeling of scene or object requires registration of multiple range scans, which are obtained by range sensor from different viewpoints. An approach is proposed for scaling registration of multiview range scans via motion averaging. First, it presents a method to estimate overlap percentages of all scan pairs involved in multiview registration. Then, a variant of iterative closest point algorithm is presented to calculate relative motions (scaling transformations) for these scan pairs, which contain high overlap percentages. Subsequently, the proposed motion averaging algorithm can transform these relative motions into global motions of multiview registration. In addition, it also introduces the parallel computation to increase the efficiency of multiview registration. Furthermore, it presents the error criterion for accuracy evaluation of multiview registration result, which can make it easy to compare results of different multiview registration approaches. Experimental results carried out with public available datasets demonstrate its superiority over related approaches.