CAJ | 학술논문

针对点云数据最近点搜索时栅格化所得空间子块大，并且在未完全找到前搜索范围需扩展一圈的问题，提出一种基于二次栅格化和扩展方向可控的快速搜索算法。采用传统分块算法一次栅格化数据空间；综合考虑非空栅格、最近点数目及一次划分边长，计算二次栅格化的边长；在局部搜索过程中控制扩展方向，优先在最有可能出现的栅格中进行搜索。实验结果表明，与现存的方法相比，该算法在搜索时间上至少减少了20％。
침대점운수거최근점수색시책격화소득공간자괴대，병차재미완전조도전수색범위수확전일권적문제，제출일충기우이차책격화화확전방향가공적쾌속수색산법。채용전통분괴산법일차책격화수거공간；종합고필비공책격、최근점수목급일차화분변장，계산이차책격화적변장；재국부수색과정중공제확전방향，우선재최유가능출현적책격중진행수색。실험결과표명，여현존적방법상비，해산법재수색시간상지소감소료20％。
For the problem of bigger sub‐block space after dividing when searching point’ s nearest neighbors and extending around search range before completing search ,a fast search algorithm based on second dividing and controlled extension direction was presented .At first ,the minimum bounding box of point cloud data was divided into a set of uniform grids by using traditional algorithms .Then the size of second divided grid was figured out by overall considering grids that were not empty ,the number of nearest neighbors and the size of first divided grid .Finally ,the most possible grids were searched preferentially through direction control in the process of local search .Compared with the existing methods ,simulation results shows that the provided algorithm can reduce searching time by 20% at least .