6806

Robust Edge Detection and GPU-Based Smoothing for Extracting Surface Primitives from Range Images

Kunihiko Ikeda, Chihiro Matsunuma, Hiroshi Masuda
The University of Tokyo
Computer-Aided Design and Applications, Volume 8, Number 4, Pages 603-616, 2011

@article{ikeda2011robust,

   title={Robust Edge Detection and GPU-Based Smoothing for Extracting Surface Primitives from Range Images},

   author={Ikeda, K. and Matsunuma, C. and Masuda, H.},

   year={2011}

}

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It is important to construct 3D virtual models of man-made fields in which people work and live. Recent mid-range and long-range laser scanners can be used to acquire 3D shapes of cities, buildings, factories, heavy goods, transportation infrastructure, and so on. However, they tend to produce outliers and very noisy points near silhouettes and sharp edges of objects. This problem makes it difficult to reconstruct bounded faces. In addition, since enormous volumes of point-clouds are captured from a broad range of scenes, efficient processing methods are required. In this paper, we propose a robust edge detection method and an efficient GPU-based smoothing method for reconstructing primitive surfaces. We first calculate straight edge lines and silhouette lines from raw scanned data, and then eliminate noises and outliers by our GPU-based smoothing method for calculating surface equations. Then primitive surfaces are extracted using sharp edges, silhouette lines and surface equations. Our method is useful to robustly extract surface primitives from practical noisy point-clouds.
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