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Journal of Information Science and Engineering, Vol. 25 No. 4, pp. 1135-1146 (July 2009)

A Feature-Preserving Filtering Algorithm for Point Set Surface and Surface Attributes Based on Robust Statistics*

Institute of Image Processing and Pattern Recognition
Shanghai Jiaotong University
Shanghai, 200240 China
+INSA-Lyon, Villeurbanne, F-69621, France
Universite de Lyon
Lyon, F-69003, France

With the increasing use of three-dimensional (3D) scanning tools and corresponding growth in the number and complexity of scanned objects or models, there is an increasing need in the development of robust and efficient processing techniques for scanned raw data, also referred to as point set surface and surface attributes. We present a features-preserving filtering algorithm for point set surface and surface attributes. The proposed approach is based on robust statistics, by constructing robust prediction framework for first-order estimation of points and surface attributes. Experiments show that the proposed approach preserves the sharp features and the edges of surface attributes while smoothing point set surface and corresponding attributes.

Keywords: point set surface, robust statistics, denoising, bilateral filtering, weighted least square method

Full Text () Retrieve PDF document (200907_11.pdf)

Received August 20, 2007; revised October 30, 2007; accepted March 27, 2008.
Communicated by Tong-Yee Lee.
* This work was partly supported by the Program of Advance Research between France and Chinese (PRA SI 03-03), the Region Rhone-Alpes of France within the project "MIRA Research 2003" and the Project of Image Guided Surgery of Shanghai, China (045115001). "Portions of the research in this paper use the BJUT- 3D Face Database collected under the joint sponsor of National Natural Science Foundation of China, Beijing Natural Science Foundation Program, Beijing Science and Educational Committee Program" and a citation to "The BJUT-3D Large-Scale Chinese Face Database".