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A 3D modeling methodology based on a concavity-aware geometric test to create 3D textured coarse models from concept art and orthographic projections
- Source :
- Computers & Graphics. 76:73-83
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- Creating textured 3D meshes of objects for real-time applications can be a laborious, slow and expensive task, demanding specific, highly specialized human resources such as 2D and 3D artists. In this paper, we present a fully automatic 3D modeling methodology based on silhouette carving, capable of creating textured 3D meshes from three pieces of concept art. Our method takes a set of the target object concept art in different views as input and generates a coarse 3D mesh alongside a diffuse color map for texturing the model. The coarse mesh is intended to replace the initial primitive mesh used on the modeling technique known as Box Modeling to accelerate the whole 3D model production. Although, in current 3D model production pipeline there are some more sophisticated methods based on sculpting and retopology, Box Modeling is still a heavily adopted technique used for man-made objects that do not require organic modeling. Our experiments show that it speeds up the 3D content production time up to 40% by providing the coarse model automatically. Also, our method preserve the artist’s trace and can create more accurate meshes compared to a similar approach, photoconsistency-based, and learning-based methods.
- Subjects :
- Carving
business.industry
Computer science
Orthographic projection
General Engineering
020207 software engineering
02 engineering and technology
3D modeling
Object (computer science)
Computer Graphics and Computer-Aided Design
Silhouette
Human-Computer Interaction
Set (abstract data type)
Computer graphics (images)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Polygon mesh
business
ComputingMethodologies_COMPUTERGRAPHICS
TRACE (psycholinguistics)
Subjects
Details
- ISSN :
- 00978493
- Volume :
- 76
- Database :
- OpenAIRE
- Journal :
- Computers & Graphics
- Accession number :
- edsair.doi...........bf93e4156a6be0c98a8aa806be50e998
- Full Text :
- https://doi.org/10.1016/j.cag.2018.09.002