Applying an artificial neural network to building reconstruction
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
3D line segment detection for unorganized point clouds from multi-view stereo
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
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3D line segment can be regarded as one of the most useful features in constructing 3D model. In this context, this paper presents a new 3D line segment extraction method by using line fitting of elevation data on 2D line coordinates of ortho-image. In order to use elevation in line fitting, the elevation itself should be reliable. To measure the reliability of elevation, in this paper, we employ the concept of self-consistency. We test the effectiveness of the proposed method with a quantitative accuracy analysis using synthetic images generated from Avenches data set of Ascona aerial images. Experimental results indicate that our method generates 3D line segments almost 10 times more accurate than raw elevations obtained by area-based method.