Name
Abstract | ||
|---|---|---|
To date the methods to create accuracy dense realistic 3D models of outdoors by using laser scanners are highly dependent on the on-site conditions in the very moment of the 3D data collection. Thus, researchers put in a lot of effort on eliminating colour incoherencies (sunny/shady, bright/dark, non sensed areas, etc.) or modelling the light of the scene to obtain free-illumination models. This paper proposes a new strategy that aims to separate the moments in which geometry and colour are taken, making the modelling process independent of the time and external circumstances in the data collection stage, and on-site calibration-free. Our approach is based on matching anytime suitable external images of the scene into the complete 3D geometric model and carrying out an iterative weighted colour mixing algorithm which gradually builds the textured model. The method has been mainly tested in archaeological sites; particularly in rest of ancient Roman buildings, yielding excellent results. Comparison with other commercial solutions is also shown in the paper. |
Year | Venue | Keywords |
|---|---|---|
2012 | ICPR | scene light modelling,archaeological sites,laser scanners,image matching,scene geometry,free-illumination models,3d geometric model,optical scanners,colour incoherency elimination,roman ancient buildings,on-site calibration-free modelling process,dense realistic 3d model creation method,realistic images,external image matching,iterative weighted colour mixing algorithm,natural scenes,archaeology,solid modelling,image texture,iterative methods,image colour analysis,3d data collection |
Field | DocType | ISSN |
Optical scanners,Computer graphics (images),Computer science,Solid modelling,Artificial intelligence,Geometry,Data collection,Computer vision,Image texture,Image matching,Iterative method,Geometric modeling,Decoupling (cosmology) | Conference | 1051-4651 |
ISBN | Citations | PageRank |
978-1-4673-2216-4 | 0 | 0.34 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Adán | 1 | 124 | 22.27 |
| Pilar Merchán | 2 | 63 | 11.05 |
| Santiago Salamanca | 3 | 63 | 11.24 |