Abstract - An automatic 3D model retrieval from freehand conceptual sketches is a key target for both commercial software houses and academic research. Unfortunately, most of the approaches are not suitable for properly translating stylistic sketches into 3D models. In order to carry out this 3D model conversion, the first task to be dealt with is to turn raster data (3D or 2D free-form curves) into vectorial ones. Such a task represents a key issue which has been addressed by a number of authors but still far to be exhaustively worked out. To address this challenge, this work presents a new method that allows to fit 2D unordered point cloud data with Multiple Incident Splines (MISs). At the heart of the proposed approach are two main procedures: the first one is based on Euclidean Minimum Spanning Tree (EMST) and Principal Component Analysis (PCA) for detecting the main local directions of the point cloud and to order its points while preserving original topology; the second is meant to fit ordered point clouds with spline curves providing a robust intersection and vertex detection. The proposed methodology, tested on a number of case studies, proves to preserve the original topology more efficiently than alternative techniques supplied by commercial vectorization software packages.

Multiple Incident Splines (MISs) algorithm for topological reconstruction of 2D unordered point clouds / R.Furferi;L.Governi;M.Palai;Y.Volpe. - In: INTERNATIONAL JOURNAL OF MATHEMATICS AND COMPUTERS IN SIMULATION. - ISSN 1998-0159. - ELETTRONICO. - 5(2):(2011), pp. 171-179.

Multiple Incident Splines (MISs) algorithm for topological reconstruction of 2D unordered point clouds

FURFERI, ROCCO;GOVERNI, LAPO;PALAI, MATTEO;VOLPE, YARY
2011

Abstract

Abstract - An automatic 3D model retrieval from freehand conceptual sketches is a key target for both commercial software houses and academic research. Unfortunately, most of the approaches are not suitable for properly translating stylistic sketches into 3D models. In order to carry out this 3D model conversion, the first task to be dealt with is to turn raster data (3D or 2D free-form curves) into vectorial ones. Such a task represents a key issue which has been addressed by a number of authors but still far to be exhaustively worked out. To address this challenge, this work presents a new method that allows to fit 2D unordered point cloud data with Multiple Incident Splines (MISs). At the heart of the proposed approach are two main procedures: the first one is based on Euclidean Minimum Spanning Tree (EMST) and Principal Component Analysis (PCA) for detecting the main local directions of the point cloud and to order its points while preserving original topology; the second is meant to fit ordered point clouds with spline curves providing a robust intersection and vertex detection. The proposed methodology, tested on a number of case studies, proves to preserve the original topology more efficiently than alternative techniques supplied by commercial vectorization software packages.
2011
5(2)
171
179
R.Furferi;L.Governi;M.Palai;Y.Volpe
File in questo prodotto:
File Dimensione Formato  
published.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: Open Access
Dimensione 1.31 MB
Formato Adobe PDF
1.31 MB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/500056
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? ND
social impact