Object representations at multiple scales from digital elevation models

Correlation scales of digital elevation models in developed coastal environments

Fusion of Digital Elevation Models Using Sparse Representations

Nowadays, different sensors and processing techniques provide Digital Elevation Models (DEMs) for the same site, which differ significantly with regard to their geometric characteristics and accuracy. Each DEM contains intrinsic errors due to the primary data acquisition technology, the processing chain, and the characteristics of the terrain. DEM fusion aims at overcoming the limitations of di...

Building extraction from digital elevation models

To extract buildings from Digital Elevation Models, we define a point process whose points represent buildings. We then define a density for this point process which is split into two parts, consisting in an ”internal field” that allows us to model the prior knowledge we have on patterns of buildings in urban areas and an ”external field” that makes the point process fit the data. We then use a...

Digital Elevation Models from Contour Lines

♦ Sampling density along the contours Interpolation of the irregular set of data points to a regular grid Valid theorems for sampling density have only recently been developed. Interpolation methods have to deal with the 'flat triangle' problem, as well as preservation of the accuracy of slope. Meaningful slopes are increasingly important in applications such as soil erosion and run-off modelli...

Free-Form 3-D Object Recognition at Multiple Scales

The recognition of free-form 3-D objects using multi-scale features recovered from 3-D models, and based on the geometric hashing algorithm and global veri cation is presented. The feature points on the object are detected by smoothing its surface after construction of semigeodesic coordinates at each point (mesh vertex). This technique is the generalisation of the CSS method which is a powerfu...