## 1 Introduction  
The modelling of indoor areas of existing buildings is a huge issue since the emergence of Building Information Modelling (BIM) in Architecture, Engineering and Construction (AEC) industry. [PERSON] et al. [1] highlight the fact that despite well established BIM processes for new buildings, the majority of existing buildings is not maintained, refurbished or deconstructed with BIM yet. According to [PERSON] and [PERSON] [2], the need to refurbish the cultural heritage is becoming more important than the construction of new buildings. The potential benefits of BIM implementation in existing buildings seem to be significant, for among them, restoration, documentation, maintenance, quality control or energy and space management [1, 3]. The creation of a Building Information Model of an existing building commonly named as-built BIM requires the acquisition of the as-is state of the building. Terrestrial Laser Scanning (TLS) is widely used to achieve this goal. Indeed, laser scanners permit to collect information about object geometry in form of point clouds. They provide a large amount of accurate data in a very fast way and with a high level of details [4; 5; 6]. Some governments such as the British and the American governments recommend the use of this capture technology in the BIM process [7; 8].  
Unfortunately, the scan-to-BIM process remains largely a manual process because of the huge amount of data, the challenge that constitutes the reconstruction of occluded parts of buildings and the absence of semantic information in point clouds. This is time consuming and requires skills. A key challenge today is thus to automate the process leading to as-built BIM from point clouds. The aim of our project is to develop a processing chain allowing to extract automatically the maximum of information from point clouds in order to integrate easily the result in BIM software. Three items were considered for the development of the approach. The first item is the automation. A 3D semi-automatic reconstruction is proposed and tasks which can be automated have to be identified. Secondly, in order to guaranty the generalisation of the approach, a transferability item is considered. It involves the definition of characteristics of studied buildings. The last but not least item is the geometric quality of the results. Quality criteria are intended to be integrated in the approach and quality indexes have to be proposed for the inspection of reconstruction results.  
In this article, a state of the art of the process which consists in the creation of as-built BIM from point clouds is first proposed (Section 2). The Section 3 is dedicated to the full description of the developed approach which considers indoor point clouds as input. The project framework is presented and the two parts of the approach, namely the segmentation of building elements point clouds and the 3D reconstruction of walls and slabs of buildings, are detailed. The assessment of the developed approach is then considered in Section 4. Datasets and thresholds used for the assessment are presented and results of both parts of the approach are shown. Moreover, quality indexes are introduced for the inspection of results. Finally, some future works are proposed and new trends for as-built BIM creation are discussed (Section 5).