A signal processing approach to fair surface design
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Progressive geometry compression
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
ACM SIGGRAPH 2003 Papers
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
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Recently developed methods address the problem of denoising polygonal meshes derived from automatic scanning procedures. Nonlinear filtering is applied iteratively based on the estimated statistical properties of errors associated with the measured vertex locations. This procedure requires a rather uniform sampling interval across the surface and cannot remove noise below a certain frequency due to the local support of the filter kernel. We consider an approach to remedy these problems by interleaving mesh denoising and mesh simplification based on the quadric error metric. Instead of directly operating on vertex locations, the error quadrics (which are evaluated to determine vertex locations) are manipulated. Therefore denoising is applied at different scales according to the progress of simplification, being less sensitive to varying resolution and low-frequency noise. This is work in progress, which reveals some interesting properties in the context of denoising and simplification. However, the desired results have not yet been achieved.