Coarse to fine : toward an intelligent 3D acquisition system
| Autor: | Olivier Aubreton, Frederic Truchetet, Vincent Daval |
|---|---|
| Přispěvatelé: | Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, SPIE, Daval, Vincent, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Computer science
business.industry [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Object (computer science) 3D modeling [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Set (abstract data type) 3D primitive extraction [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Chain (algebraic topology) Object model normal estimate Computer vision Stage (hydrology) Artificial intelligence business 3D acquisition 3D compression |
| Zdroj: | Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015 Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015, SPIE, Feb 2015, San Francisco, United States Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015, Feb 2015, San Francisco, United States. 9393, 2015 Three-Dimensional Image Processing, Measurement (3DIPM), and Applications |
| Popis: | International audience; The 3D acquisition-compression-processing chain is , most of the time , sequenced into independent stages. As resulting , a large amount of 3D points are acquired whatever the geometry of the object and the processing to be done in further steps. It appears , particularly in mechanical part 3D modeling and in CAD , that the acquisition of such an amount of data is not always mandatory. We propose a method aiming at minimizing the number of 3D points to be acquired with respect to the local geometry of the part and therefore to compress the cloud of points during the acquisition stage. The method we propose is based on a new coarse to fine approach in which from a coarse set of 2D points associated to the local normals the 3D object model is segmented into a combination of primitives. The obtained model is enriched where it is needed with new points and a new primitive extraction stage is performed in the refined regions. This is done until a given precision of the reconstructed object is attained. It is noticeable that contrary to other studies we do not work on a meshed model but directly on the data provided by the scanning device . |
| Databáze: | OpenAIRE |
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