NDLI: Mesh Representation Driven by Variance Normalized Neighborhood in Scale Space

Content Provider	IEEE Xplore Digital Library
Author	Cheng, I. Daniilidis, K.
Copyright Year	2008
Description	Author affiliation: Comput. & Inf. Sci., Univ. of Pennsylvania, Philadelphia, PA (Cheng, I.; Daniilidis, K.)
Abstract	In this paper, we extend our previous work on regular mesh simplification using scale-space filtering (SSF), to arbitrary meshes. Additional challenges in using arbitrary meshes involve accurately defining a geodesic distance and a structure attribute. Since our SSF method is based on Laplacian smoothing, which filters finer local details before larger global structures, it preserves perceptual quality that is consistent with how the human visual system looks at 3D objects moving from close to farther away. By keeping the simplified mesh vertices as a subset of the denser meshes, versus using the vertex split operation, bandwidth is utilized more efficiently during refinement. Our contribution lies in applying the shortest path normalized by variance, instead of using an un-normalized geodesic distance to weight the influence of a neighborhood. Variance normalization ensures that the global smoothing property is preserved. We build a priority list to facilitate vertex removal and insertion. Experimental results are presented to support our approach.
Starting Page	329
Ending Page	332
File Size	307206
Page Count	4
File Format	PDF
ISBN	9781424417605
DOI	10.1109/3DTV.2008.4547875
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-28
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Smoothing methods Laplace equations Filtering mesh compression, Humans level-of-detail Mesh representation Convergence Information science Visual system Filters Bandwidth scale-space perceptual quality Mesh generation
Content Type	Text
Resource Type	Article

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