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http://dx.doi.org/10.7848/ksgpc.2017.35.4.303

Development of Classification Technique of Point Cloud Data Using Color Information of UAV Image  

Song, Yong-Hyun (Dept. of Civil Engineering, Korea National University of Transportation)
Um, Dae-Yong (Dept. of Civil Engineering, Korea National University of Transportation)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.35, no.4, 2017 , pp. 303-312 More about this Journal
Abstract
This paper indirectly created high density point cloud data using unmanned aerial vehicle image. Then, we tried to suggest new concept of classification technique where particular objects from point cloud data can be selectively classified. For this, we established the classification technique that can be used as search factor in classifying color information in point cloud data. Then, using suggested classification technique, we implemented object classification and analyzed classification accuracy by relative comparison with self-created proof resource. As a result, the possibility of point cloud data classification was observable using the image's information. Furthermore, it was possible to classify particular object's point cloud data in high classification accuracy.
Keywords
Unmanned Aerial Vehicle; Point Cloud Data; Classification; Color Information;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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