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

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Weinmann, M. and Mallet, C. and Bredif, M. (2016) Detection, segmentation and localization of individual trees from mms point cloud data. In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) .

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Event: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC)
Abstract: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.
Item Type:Conference or Workshop Item (Paper)
Link to this item:https://doi.org/10.3990/2.388
Conference URL:https://www.geobia2016.com/
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