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基于稀疏点云的多平面场景稠密重建

DOI: 10.16383/j.aas.2015.c140279, PP. 813-822

Keywords: 多视重建,三维重建,多模型估计,图像分割

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Abstract:

?多平面场景是生活中常见的一种场景,然而由于该类场景中常常存在物体表面纹理缺乏和纹理重复的现象,导致从多视图像重建获得的三维点云数据中存在点云过于稀疏甚至孔洞等问题,进而导致以微面片拟合三维点云所得到的重建表面出现平面颠簸现象.针对这些问题,本文提出了一种基于稀疏点云的分段平面场景重建方法.首先,利用分层抽样代替随机抽样,改进了J-Linkage多模型估计算法;然后,利用该方法对稀疏点云进行多平面拟合,来获得场景的多平面模型;最后,将多平面模型和无监督的图像分割相结合,提取并重建场景中的平面区域.场景中的非平面部分用CMVS/PMVS(Clusteringviewsformulti-viewstereo/patch-basedmulti-viewstereo)算法重建.多平面模型估计的实验表明,改进的J-Linkage算法提高了模型估计的准确度.三维重建的实验证实,提出的重建方法在有效地克服孔洞和平面颠簸问题的同时,还能重建出完整平面区域.

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