Mobile mapping laser scanning systems have become more and more widespread for the acquisition of millions of 3D points on large and geometrically complex urban sites. Vehicle-based Laser Scanning (VLS) systems travel many kilometers while acquiring raw point clouds which are registered in real time in a common coordinate system. Improvements of the acquisition steps as well as the automatic processing of the collected point clouds are still a conundrum for researchers. This paper shows some results obtained by application, on mobile laser scanner data, of segmentation and reconstruction algorithms intended initially to generate individual vector facade models using stationary Terrestrial Laser Scanner (TLS) data. The operating algorithms are adapted so as to take into account characteristics of VLS data. The intrinsic geometry of a point cloud as well as the relative geometry between registered point clouds are different from that obtained by a static TLS. The amount of data provided by this acquisition technique is another issue. Such particularities should be taken into consideration while processing this type of point clouds. The segmentation of VLS data is carried out based on an adaptation of RANSAC algorithm. Edge points of each element are extracted by applying a second algorithm. Afterwards, the vector models of each facade element are reconstructed. In order to validate the results, large samples with different characteristics have been introduced in the developed processing chain. The limitations as well as the capabilities of each process will be emphasized in terms of geometry and processing time.