红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2014年
4期
1316-1321
,共6页
相似性%三维点云%质心%特征向量
相似性%三維點雲%質心%特徵嚮量
상사성%삼유점운%질심%특정향량
similarity%3-D point clouds%center of mass%feature vector
提出一种基于子空间特征向量的三维点云相似性分析算法。首先，获取两个物体的三维点云数据，并进行位置标准化。其次，利用最小子空间分割算法将两个三维点云分别分割成若干子空间。随后，计算子空间的质心到其拟合曲面的距离和夹角，并基于上述距离和夹角构成的向量空间，提取子空间特征向量。最后，通过特征向量间的相似度计算来评价两个三维点云的相似性。由于该方法将描述三维形体特征的子空间特征向量作为相似度度量的依据，所以具有数据量小、精度高的特点。实验表明，该算法能够定量地分析两个三维物体的相似性。
提齣一種基于子空間特徵嚮量的三維點雲相似性分析算法。首先，穫取兩箇物體的三維點雲數據，併進行位置標準化。其次，利用最小子空間分割算法將兩箇三維點雲分彆分割成若榦子空間。隨後，計算子空間的質心到其擬閤麯麵的距離和夾角，併基于上述距離和夾角構成的嚮量空間，提取子空間特徵嚮量。最後，通過特徵嚮量間的相似度計算來評價兩箇三維點雲的相似性。由于該方法將描述三維形體特徵的子空間特徵嚮量作為相似度度量的依據，所以具有數據量小、精度高的特點。實驗錶明，該算法能夠定量地分析兩箇三維物體的相似性。
제출일충기우자공간특정향량적삼유점운상사성분석산법。수선，획취량개물체적삼유점운수거，병진행위치표준화。기차，이용최소자공간분할산법장량개삼유점운분별분할성약간자공간。수후，계산자공간적질심도기의합곡면적거리화협각，병기우상술거리화협각구성적향량공간，제취자공간특정향량。최후，통과특정향량간적상사도계산래평개량개삼유점운적상사성。유우해방법장묘술삼유형체특정적자공간특정향량작위상사도도량적의거，소이구유수거량소、정도고적특점。실험표명，해산법능구정량지분석량개삼유물체적상사성。
This paper presents a method of similarity analysis algorithm of the three-dimensional point cloud,which is based on eigenvector of the subspace. First of all, the three-dimensional point cloud data of two objects were obtained and positions of them were standardized. And then, the two three-dimensional point clouds were divided into several subspace by using the minimal spatial segmentation algorithm. Thirdly, the eigenvector of subspace were calculated, which should be divided into two steps:the first step was to calculate distance and angle from the centroid to the subspace surface, the next step was to compute the new eigenvector on the basis of vector space, which was composed of the distance and angle in step one. This research method took the advantage of small data in quantity and high precision in calculation because the eigenvector of subspace, which can describe the three-dimensional characteristics as the basis of similarity measure. The experiment shows that the algorithm can quantitatively analyze the similarity of two three-dimensional objects.
