6533b861fe1ef96bd12c4dba
RESEARCH PRODUCT
Generic attribute deviation metric for assessing mesh simplification algorithm quality
Frederic TruchetetSebti FoufouMichaël Roysubject
Computationmedia_common.quotation_subjectFeature extraction[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]02 engineering and technologySolid modeling[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Computer graphics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringQuality (business)Polygon meshComputingMethodologies_COMPUTERGRAPHICSmedia_commonMathematicsbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionComputational geometry[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR][INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]Metric (mathematics)020201 artificial intelligence & image processingArtificial intelligencebusinessAlgorithmdescription
International audience; This paper describes an efficient method to compare two triangular meshes. Meshes considered here contain geometric features as well as other surface attributes such as material colors, texture, temperature, radiation, etc. Two deviation measurements are presented to assess the differences between two meshes. The first measurement, called geometric deviation, returns geometric differences. The second measurement , called attribute deviation, returns attribute differences regardless of the attribute type. In this paper we present an application of this method to the Mesh Simplification Algorithm (MSA) quality assessment according to the appearance attributes. This assessment allows the appreciation of local quality and the computation of global quality statistics of a simplified mesh.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2002-09-01 | Proceedings. International Conference on Image Processing |