室内3D点云模型的门窗检测.

Shen, Le; Li, Guiqing; Xian, Chuhua; Jiang, Yang; Xiong, Yunhui

Abstract

This paper proposes a 3D-2D-3D algorithm for doors and windows detection in 3D indoor environment of point cloud data. Firstly, by setting up a virtual camera in the middle of this 3D environment, a set of pictures are taken from different angles by rotating the camera, so that corresponding 2D images can be generated. Next, these images are used to detect and identify the positions of doors and windows in the space. To obtain point cloud data containing the doors and windows position information, the 2D information are then mapped back to the origin 3D point cloud environment. Finally, by processing the contour lines and crossing points, the features of doors and windows through the position information are optimized. The experimental results show that this "global-local" approach is efficient when detecting and identifying the location of doors and windows in 3D point cloud environment. The full text of this article is in Chinese.

Citation

SHEN, L., LI, G., XIAN, C., JIANG, Y. and XIONG, Y. 2019. 室内3D点云模型的门窗检测. Jisuanji fuzhu sheji yu tuxingxue xuebao/Journal of computer-aided design and computer graphics [online], 31(9), pages 1494-1501. Available from: https://doi.org/10.3724/SP.J.1089.2019.17575

• Journal Article Type: Article
• Acceptance Date: Aug 19, 2019
• Online Publication Date: Aug 19, 2019
• Publication Date: Sep 30, 2019
• Deposit Date: Mar 6, 2020
• Publicly Available Date: Mar 6, 2020
• Journal: Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics
• Print ISSN: 1003-9775
• Publisher: Institute of Computing Technology of the Chinese Academy of Sciences
• Peer Reviewed: Peer Reviewed
• Volume: 31
• Issue: 9
• Pages: 1494-1501
• DOI: https://doi.org/10.3724/SP.J.1089.2019.17575
• Keywords: Door and window detection; Feature corner points; Indoor scene; Object detection; Point cloud
• Public URL: https://rgu-repository.worktribe.com/output/766807
• Publisher URL: http://new.oversea.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFDLAST2019&filename=JSJF201909004