Automatic segmentation of LiDAR point cloud data at different height levels for 3D building extraction

S. M. Abdullah, Mohammad Awrangjeb, Guojun Lu

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

    9 Citations (Scopus)


    This paper presents a new LiDAR segmentation technique for automatic building detection and roof plane extraction. First, it uses a height threshold, based on the digital elevation model it divides the LiDAR point cloud into 'ground' and 'non-ground' points. Then, starting from the maximum LiDAR height, and decreasing the height at each iteration, it looks for points to form planar roof segments. At each height level, it clusters the points based on the distance and finds straight lines using the points. The nearest coplanar point to the midpoint of each line is used as a seed point and the plane is grown in a region growing fashion. Finally, a rule-based procedure is followed to remove planar segments in trees. The experimental results show that the proposed technique offers a high building detection and roof plane extraction rates while compared to other recently proposed techniques.

    Original languageEnglish
    Title of host publication2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW 2014)
    Subtitle of host publicationChengdu, China, 14-18 July 2014 [Proceedings]
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Number of pages6
    ISBN (Electronic)9781479947171
    ISBN (Print)9781479947164
    Publication statusPublished - 3 Sept 2014
    EventIEEE International Workshop on Hot Topics in 3D 2014 - Chengdu, China
    Duration: 14 Jul 201414 Jul 2014
    Conference number: 5th (listing of all the workshops held at ICME 2014)


    WorkshopIEEE International Workshop on Hot Topics in 3D 2014
    Abbreviated titleHot3D 2014
    OtherHeld in conjunction with ICME'14
    (14 workshops)
    Internet address


    • Building detection
    • height levels
    • LiDAR
    • roof plane extraction

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