Simultaneous mesh simplification and noise smoothing of range images

D. L. Page, Y. Sun, A. F. Koschan, J. K. Paik, M. A. Abidi

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

In this paper, we propose a novel algorithm to smooth and simplify simultaneously range images and also triangle meshes derived from those images. These data sets often suffer from noise and over-sampling. To overcome these issues, smoothing from image processing and simplification from computer graphics attempt to minimize noise and reduce complexity, respectively. Typically, these algorithms are separate and distinct steps, but we combine them into one algorithm. We employ surface normal voting to generate robust orientation estimates and then extend the quadric error metric framework to smooth noise while simplifying the surface. We demonstrate the capabilities of this algorithm with both synthetic and real data. The proposed algorithm provides significant noise smoothing improvement when compared to the standard Garland and Heckbert quadric simplification algorithm.

Original languageEnglish
PagesIII/821-III/824
StatePublished - 2002
EventInternational Conference on Image Processing (ICIP'02) - Rochester, NY, United States
Duration: Sep 22 2002Sep 25 2002

Conference

ConferenceInternational Conference on Image Processing (ICIP'02)
Country/TerritoryUnited States
CityRochester, NY
Period09/22/0209/25/02

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