It is strongly desirable to accurately detect the clouds in hyperspectral images onboard 1 before compression. However, conventional onboard cloud detection methods are not appropriate 2 to all situation such as shadowed cloud or darken snow covered surfaces which are not identified 3 properly in the NDSI test. In this paper, we propose a new spectral–spatial classification strategy to 4 enhanc...

In my PhD thesis Segmentation and Approximation of large point clouds I created an new approach for the automation of the point cloud segmentation process. Surface reconstruction or Reverse Engineering describes the process to get a mathematical representation of a measured object ( based on B-Spline surfaces ) from an unorganized set of 3D points ( point cloud ). This process is nowadays inter...

Cloud computing is an emerging concept of information technology that in many countries has an influence on many companies. The research was conducted to evaluate cloud computing adoption in Saudi Arabia; Benefits and hindrances for small and medium-sized enterprises (SMEs). The qualitative research approach is performed by interviews with the management of a variety of SMEs active in the infor...

This paper aims at façade reconstruction for subsequent enrichment of LOD2 building models. We use point clouds from dense image matching with imagery both from Mobile Mapping systems and oblique airborne cameras. The interpretation of façade structures is based on a geometric reconstruction. For this purpose a pre-segmentation of the point cloud into façade points and non-façade points is nece...

3D map building is a complex robotics task which needs mathematical robust models. From a 3D point cloud, we can use the normal vectors to these points to do feature extraction. In this paper, we propose to extract geometric primitives (e.g. planes) from the cloud. We will present a robust method for normal estimation.

The cloud point of copolymers of 2-ethyl-2-oxazoline and 2-n-propyl-2-oxazoline could be tuned from 25 degrees C to 100 degrees C by varying molecular weight and composition; the reversibility and concentration dependence of the cloud points were evaluated to assess the potential of these copoly(2-oxazoline)s as alternatives to poly(N-isopropylacrylamide).

3D map building is a complex robotics task which needs mathematical robust models. From a 3D point cloud, we can use the normal vectors to these points to do feature extraction. In this paper, we will present a robust method for normal estimation and unconstrained 3D-mesh generation from a not-uniformly distributed point cloud.

Point clouds from multi-looking oblique view airborne laser scanning can provide information about building façades, not only for a single building but also for a larger urban area. This has the disadvantage of a reduced point density. To gain window information for building models from that data an approach has to be developed which can cope with a point cloud with low resolution (around 10 po...

Going from unstructured cloud of points to surfaces is a challenging problem. However, as points are produced by a structure-and-motion pipeline, image-consistency is a powerful clue that comes to the rescue. In this paper we present a method for extracting planar patches from an unstructured cloud of points, based on the detection of image-consistent planar patches with J-linkage, a robust alg...