Detection, segmentation and localization of individual trees from MMS point cloud data

M. Weinmann, Clément Mallet, Mathieu Bredif

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In this paper, we address the extraction of objects from 3D point clouds acquired with mobile mapping systems. More specifically, we focus on the detection of tree-like objects, a subsequent segmentation of individual trees and a localization of the respective trees. Thereby, the detection of tree-like objects is achieved via a binary point-wise classification based on geometric features, which categorizes each point of the 3D point cloud into either tree-like objects or non-tree-like objects. The subsequent segmentation and localization of individual trees is carried out by applying a 2D projection and a mean shift segmentation on a downsampled version of that part of the original 3D point cloud which represents all tree-like objects, and it also involves a segment-based shape analysis to only retain plausible tree segments. We demonstrate the performance of our framework on a benchmark dataset which contains 10.13M 3D points and has been acquired with a mobile mapping system in the city of Delft in the Netherlands.
Original languageEnglish
Title of host publicationProceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands
EditorsN. Kerle, M. Gerke, S. Lefevre
Place of PublicationEnschede
PublisherUniversity of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)
Number of pages8
ISBN (Print)978-90-365-4201-2
Publication statusPublished - 14 Sept 2016
Externally publishedYes
Event6th International Conference on Geographic Object-Based Image Analysis, GEOBIA 2016: Solutions & Synergies - University of Twente Faculty of Geo-Information and Earth Observation (ITC), Enschede, Netherlands
Duration: 14 Sept 201616 Sept 2016
Conference number: 6


Conference6th International Conference on Geographic Object-Based Image Analysis, GEOBIA 2016
Abbreviated titleGEOBIA
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