This paper presents a region-based method for extraction of consistent surfaces from raw point clouds. The method uses a new robust estimation method of constructing seed regions and a new method of orientating region...This paper presents a region-based method for extraction of consistent surfaces from raw point clouds. The method uses a new robust estimation method of constructing seed regions and a new method of orientating regions or surfaces. The robust estima- tion method selects good seed regions from candidate regions generated randomly in a structured neighborhood. The orienta- tion method uses transition vectors from which include angles of adjacent normal vectors are not greater than 90~ and thus can be orientated correctly crossing sharp features or close-by opposite surfaces. The region-based method consists of two levels of segmentation： planar segmentation and quadric segmentation, both of which produce consistent surfaces. The quadric segmen- tation fits general quadrics by 3 L fitting algorithm in its region growing process and can take consistent planar surfaces as ini- tials. Experimental results show that the robust estimation method has higher probability of success than the traditional one and the orientation method works well. Experimental results also demonstrate the applicability of our method to various data.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51205332)the SRF for the Returned Overseas Chinese Scholars
文摘This paper presents a region-based method for extraction of consistent surfaces from raw point clouds. The method uses a new robust estimation method of constructing seed regions and a new method of orientating regions or surfaces. The robust estima- tion method selects good seed regions from candidate regions generated randomly in a structured neighborhood. The orienta- tion method uses transition vectors from which include angles of adjacent normal vectors are not greater than 90~ and thus can be orientated correctly crossing sharp features or close-by opposite surfaces. The region-based method consists of two levels of segmentation： planar segmentation and quadric segmentation, both of which produce consistent surfaces. The quadric segmen- tation fits general quadrics by 3 L fitting algorithm in its region growing process and can take consistent planar surfaces as ini- tials. Experimental results show that the robust estimation method has higher probability of success than the traditional one and the orientation method works well. Experimental results also demonstrate the applicability of our method to various data.
