3D Modeling from Photos Given Topological Information
Reconstructing 3D models given a single-view 2D information is inherently an ill-posed problem and requires additional information such as shape prior or user input.We introduce a method to generate multiple 3D models of a particular category given corresponding photographs when the topological info...
| Publié dans: | IEEE transactions on visualization and computer graphics. - 1996. - 22(2016), 9 vom: 07. Sept., Seite 2070-81 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2016
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| Accès à la collection: | IEEE transactions on visualization and computer graphics |
| Sujets: | Journal Article |
| Résumé: | Reconstructing 3D models given a single-view 2D information is inherently an ill-posed problem and requires additional information such as shape prior or user input.We introduce a method to generate multiple 3D models of a particular category given corresponding photographs when the topological information is known. While there is a wide range of shapes for an object of a particular category, the basic topology usually remains constant.In consequence, the topological prior needs to be provided only once for each category and can be easily acquired by consulting an existing database of 3D models or by user input. The input of topological description is only connectivity information between parts; this is in contrast to previous approaches that have required users to interactively mark individual parts. Given the silhouette of an object and the topology, our system automatically finds a skeleton and generates a textured 3D model by jointly fitting multiple parts. The proposed method, therefore, opens the possibility of generating a large number of 3D models by consulting a massive number of photographs. We demonstrate examples of the topological prior and reconstructed 3D models using photos |
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| Description: | Date Completed 19.06.2017 Date Revised 19.06.2017 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0506 |
| DOI: | 10.1109/TVCG.2015.2505307 |