An automatic segmentation method for building facades from vehicle-borne LiDAR point cloud data based on fundamental geographical data

Yongqiang Li; Jie Mao; Lailiang Cai; Xitong Zhang; Lixue Li

doi:10.1117/12.2234691

2 March 2016 An automatic segmentation method for building facades from vehicle-borne LiDAR point cloud data based on fundamental geographical data

Yongqiang Li, Jie Mao, Lailiang Cai, Xitong Zhang, Lixue Li

Author Affiliations +

Proceedings Volume 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015); 990102 (2016) https://doi.org/10.1117/12.2234691
Event: 2015 ISPRS International Conference on Computer Vision in Remote Sensing, 2015, Xiamen, China

Abstract

In this paper, the author proposed a segmentation method based on the fundamental geographic data, the algorithm describes as following: Firstly, convert the coordinate system of fundamental geographic data to that of vehicle- borne LiDAR point cloud though some data preprocessing work, and realize the coordinate system between them; Secondly, simplify the feature of fundamental geographic data, extract effective contour information of the buildings, then set a suitable buffer threshold value for building contour, and segment out point cloud data of building facades automatically; Thirdly, take a reasonable quality assessment mechanism, check and evaluate of the segmentation results, control the quality of segmentation result. Experiment shows that the proposed method is simple and effective. The method also has reference value for the automatic segmentation for surface features of other types of point cloud.

Citation Download Citation

Yongqiang Li, Jie Mao, Lailiang Cai, Xitong Zhang, and Lixue Li "An automatic segmentation method for building facades from vehicle-borne LiDAR point cloud data based on fundamental geographical data", Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 990102 (2 March 2016); https://doi.org/10.1117/12.2234691

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available