6533b85cfe1ef96bd12bc12e
RESEARCH PRODUCT
HIGH QUALITY TEXTURE MAPPING PROCESS AIMED AT THE OPTIMIZATION OF 3D STRUCTURED LIGHT MODELS
Y. AlognaLaura InzerilloF. Di Paolasubject
lcsh:Applied optics. Photonics010504 meteorology & atmospheric sciencesComputer scienceMesh parameterizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyTexture Mapping Structured Light Scanning Restoration 3D Visualization Photogrammetry 3D modeling01 natural scienceslcsh:Technology0202 electrical engineering electronic engineering information engineeringSegmentationComputer visionImage resolution0105 earth and related environmental sciencesComputingMethodologies_COMPUTERGRAPHICSUV mappingbusiness.industrylcsh:Tlcsh:TA1501-1820020207 software engineering3D modelingVisualizationPhotogrammetrylcsh:TA1-2040RGB color modelSettore ICAR/17 - DisegnoArtificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)Texture mappingStructured lightdescription
Abstract. This article presents the evaluation of a pipeline to develop a high-quality texture mapping implementation which makes it possible to carry out a semantic high-quality 3D textured model. Due to geometric errors such as camera parameters or limited image resolution or varying environmental parameters, the calculation of a surface texture from 2D images could present several color errors. And, sometimes, it needs adjustments to the RGB or lightness information on a defined part of the texture. The texture mapping procedure is composed of mesh parameterization, mesh partitioning, mesh segmentation unwraps, UV map and projection of island, UV layout optimization, mesh packing and mesh baking. The study focuses attention to the mesh partitioning that essentially assigns a weight to each mesh, which reveals a mesh’s weight calculated by considering the flatness and distance of the mesh with respect to a chart. The 3D texture mapping has been developed in Blender and implemented in Python. In this paper we present a flowchart that resumes the procedure which aims to achieve a high-quality mesh and texture 3D model starting from the 3D Spider acquire, integrated with the SfM texture and using the texture mapping to reduce the color errors according to a semantic interpretation.
year | journal | country | edition | language |
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2019-01-31 | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |