Feature Preserving Point Set Surfaces based on Non-Linear Kernel Regression
نویسندگان
چکیده
منابع مشابه
Feature Preserving Point Set Surfaces based on Non-Linear Kernel Regression
Moving least squares (MLS) is a very attractive tool to design effective meshless surface representations. However, as long as approximations are performed in a least square sense, the resulting definitions remain sensitive to outliers, and smooth-out small or sharp features. In this paper, we address these major issues, and present a novel point based surface definition combining the simplicit...
متن کاملFeature Preserving Point Set Surfaces based on Non-Linear Kernel regression
1. Briefly summarize the paper's contributions. Does it address a new problem? Does it present a new approach? Does it show new types of results? [AS] This paper presents a new point set surface representation by combining implicit moving least squares (IMLS) with robust statistics. In particular, they explicitly derive IMLS in the local kernel regression (LKR) framework, forming the basis of...
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Based on sampling likelihood and feature intensity, in this paper, a feature-preserving denoising algorithm for point-sampled surfaces is proposed. In terms of moving least squares surface, the sampling likelihood for each point on point-sampled surfaces is computed, which measures the probability that a 3D point is located on the sampled surface. Based on the normal tensor voting, the feature ...
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چکیده ندارد.
15 صفحه اولA Feature-Preserving Filtering Algorithm for Point Set Surface and Surface Attributes Based on Robust Statistics
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 surf...
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ژورنال
عنوان ژورنال: Computer Graphics Forum
سال: 2009
ISSN: 0167-7055,1467-8659
DOI: 10.1111/j.1467-8659.2009.01388.x