计算机科学 ›› 2019, Vol. 46 ›› Issue (2): 266-270.doi: 10.11896/j.issn.1002-137X.2019.02.041
吴飞, 赵新灿, 展鹏磊, 关凌
WU Fei, ZHAO Xin-can, ZHAN Peng-lei, GUAN Ling
摘要： 在使用点云FPFH(Fast Point Feature Histograms)特征进行三维物体识别或配准时,人为主观调整邻域半径计算FPFH特征描述符具有随意性、低效性,整个过程不能自动化完成。针对该问题,提出了自适应邻域选择的FPFH特征提取算法。首先,对多对点云估算点云密度;然后,计算多个邻域半径以提取FPFH特征用于SAC-IA配准,统计配准性能最优时的半径与点云密度值,使用三次样条插值拟合法求出函数表达式,形成自适应邻域选择的FPFH特征提取算法。实验结果表明,该算法根据点云密度自适应选择合适的邻域半径,提升了FPFH特征匹配的性能,同时加快了运算速度,具有指导价值。
中图分类号:
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