ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5/W2, 163-168, 2013
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5-W2/163/2013/
doi:10.5194/isprsannals-II-5-W2-163-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
16 Oct 2013
Optimizing detection of road furniture (pole-like object) in Mobile Laser Scanner data
D. Li and S. Oude Elberink Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, the Netherlands
Keywords: Laser Scanning, LIDAR, Point Cloud, Segmentation, Classification, Processing, Algorithm Abstract. Due to the road safety problem is becoming more and more serious recent years, existing road safety assessment by using automatic method is necessary. Meanwhile, since the pole-like objects have large effect on road safety and are in high demand as facilities to be managed, the automatic pole-like objects extraction is becoming a hot issue. As a result, a robust, quick and automatic pole-like object detection algorithm in MLS data is proposed in this paper. Two datasets are tested to show performance of the proposed algorithm, it demonstrates that it is feasible to detect tree with an overall accuracy of over 92% and other pole-like object of 72% in dataset A and 82% of tree points and 75% of other pole points in dataset B.
Conference paper (PDF, 908 KB)


Citation: Li, D. and Oude Elberink, S.: Optimizing detection of road furniture (pole-like object) in Mobile Laser Scanner data, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5/W2, 163-168, doi:10.5194/isprsannals-II-5-W2-163-2013, 2013.

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