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  Statistical Learning for Shape Applications

Saleem, W., Wang, D., Belyaev, A., & Seidel, H.-P. (2006). Statistical Learning for Shape Applications. In 1st International Symposium on Shapes and Semantics (pp. 53-60). Genova, Italy: CNR.

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StatLearn_full.pdf (Any fulltext), 721KB
 
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 Creators:
Saleem, Waqar1, Author           
Wang, Danyi1, Author           
Belyaev, Alexander1, Author           
Seidel, Hans-Peter1, Author           
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1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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 Abstract: Statistical methods are well suited to the large amounts of data typically involved in digital shape applications. In this paper, we look at two statistical learning methods related to digital shape processing. The first, \textit{neural meshes}, learns the shape of a given point cloud \--- the surface reconstruction problem \--- in $O(n^2)$ time. We present an alternate implementation of the algorithm that takes $O(n\log n)$ time. Secondly, we present a simple method to automatically learn the correct orientation of a shape in an image from a database of images with correctly oriented shapes.

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Language(s): eng - English
 Dates: 2007-03-072006
 Publication Status: Issued
 Pages: -
 Publishing info: Genova, Italy : CNR
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 314643
Other: Local-ID: C125675300671F7B-F199D73592F8196BC125719900561BF0-SaleemWBS_wss2006
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Title: Untitled Event
Place of Event: Matsushima, JAPAN
Start-/End Date: 2006-06-17

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Title: 1st International Symposium on Shapes and Semantics
Source Genre: Proceedings
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Publ. Info: Genova, Italy : CNR
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 53 - 60 Identifier: -