Automated extraction of urban trees from mobile LiDAR point clouds

Fan W.; Chenglu W.; Jonathan L.

doi:10.1117/12.2234795

2 March 2016 Automated extraction of urban trees from mobile LiDAR point clouds

Fan W., Chenglu W., Jonathan L.

Proceedings Volume 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015); 99010P (2016) https://doi.org/10.1117/12.2234795
Event: 2015 ISPRS International Conference on Computer Vision in Remote Sensing, 2015, Xiamen, China

Abstract

This paper presents an automatic algorithm to localize and extract urban trees from mobile LiDAR point clouds. First, in order to reduce the number of points to be processed, the ground points are filtered out from the raw point clouds, and the un-ground points are segmented into supervoxels. Then, a novel localization method is proposed to locate the urban trees accurately. Next, a segmentation method by localization is proposed to achieve objects. Finally, the features of objects are extracted, and the feature vectors are classified by random forests trained on manually labeled objects. The proposed method has been tested on a point cloud dataset. The results prove that our algorithm efficiently extracts the urban trees.

Citation Download Citation

Fan W., Chenglu W., and Jonathan L. "Automated extraction of urban trees from mobile LiDAR point clouds", Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 99010P (2 March 2016); https://doi.org/10.1117/12.2234795

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