Andres SERNA

Semantic analysis of 3D point clouds and images

Thanks to new 3D data availability, an increasing number of geographic applications such as Google Earth, Microsoft Bing Maps, OpenStreetMaps and Geoportail is flourishing nowadays. Some of these applications do not only require to look realistic, but have also to be faithful to reality. Automatic and semi-automatic methods for semantic analysis of these data are required in order to build accurate large scale 3D city models. We work in developing automatic methods for detection, segmentation and classification of urban entities from 3D point clouds and images. Our work is developed as part of TerraMobilita project.

Segmentation of urban objects:

Classification of urban objects:

Curbs detection and accessibility analysis:

Mathematical Morphology

Adaptive Mathematical Morphology (Presentation at ISMM2013, Uppsala, Sweden):

Segmentation of elongated objects (In French, MINES ParisTech 2013, Paris, France):