摘要
由于室内场景中存在对象种类多样、物体几何信息复杂、物体密集问题,故室内场景结构重建存在着很大的挑战。首先,以“结构分析”为主线,利用改进的随机抽样一致(RANSAC)算法和均值漂移算法检测出房间布局的粗略划分。然后,在将初步划分结果转化为无向图的基础上,利用图割算法得到了房间布局的细分结果。最后,将重建的墙壁、地面与天花板信息相结合,完成了室内场景布局的总体重建。实验结果表明,利用改进后的算法和所提方法得到的重建结果更加准确、效果更好。
Due to diversity of object species,complexity of object geometric information and intensiveness of object in indoor scene such that the reconstruction of the indoor scene structure has a big challenge.First,“structure analysis”is taken as the main line,and the rough division of room layout is detected by using improved random sample consensus(RANSAC)algorithm and mean shift algorithm.Then,on the basis of transforming the preliminary division results into undirected graphs,the subdivision results of room layout are obtained by using graph-cut algorithm.Finally,the overall reconstruction of the indoor scene layout is completed by combining the reconstructed wall,floor and ceiling information.The experimental results show that the reconstruction results obtained by the improved algorithms and the proposed methods are more accurate and better.
作者
宁小娟
陆志伟
马杰
Ning Xiaojuan;Lu Zhiwei;Ma Jie(School of Computer Science and Engineering,Xi'an University of Technology,Xi'an,Shaanai 710048,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2021年第22期258-269,共12页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61871320,61872291)
国家重点研发计划(2018YFB1004905)
教育厅重点实验室项目(17JS099)。
关键词
图像处理
点云数据
室内场景
均值漂移算法
划分
布局重建
图割算法
image processing
point cloud data
indoor scenes
mean shift algorithm
division
layout reconstruction graph-cut algorithm