Indoor scene reconstruction from a sparse set of 3D shots

The use of cost-efficient and portative devices, such as the Ki-nect, has facilitated the reconstruction of indoor scenes, which has become a field of interest to many. While a large number of applications have been developed for the accurate reconstruction of a scene through efficient registration of multiple scans, the scanning of the scene by the user remains a time-consuming process. This is particularly the case when the scan must not contain any missing data. In this paper, we propose a method requiring only a few shots without any overlapping requirement, which makes the scanning process very simple and light. Given a set point clouds (shots) sparsely taken from an indoor scene, our method seeks for transformations that align the shots together, creating an alignment graph at the same time. It then searches within this graph for the set of transformations corresponding to a possible solution, providing a reconstruction of the scene. Since our method allows missing views and can find all plausible solutions, it can be used to create new scenes by assembling shots obtained from different real or virtual scenes.