Robust segmentation of raw point clouds into consistent surfaces

这份报纸从未加工的点云为一致表面的抽取论述一个基于区域的方法。方法使用构造种子区域的一个新柔韧的评价方法和面向区域或表面的一个新方法。柔韧的评价方法从在一位结构化的邻居随机产生的候选人区域选择好种子区域。从哪个包括邻近的正常向量的角度的取向方法使用转变向量不比 90 大 ? 漠瑰浩穩瑡潩 ? 敭桴摯椠 ? 桴湥愠灰楬摥琠? 灯楴業敺琠敨搠獥杩 ? 慰慲敭整獲漠 ? 桴 ? 牰捡楴慣? 敮慧楴敶倠楯獳湯 ? 慲楴? 丨剐 ? 牣獡 ? 潢 ? 湩琠楨?

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.