Registration of Heterogenous Data for Urban Modeling

Overview & Synopsis

This thesis is part of the Building Indoor/Outdoor Modeling (BIOM) project that aims at automatic, simultaneous indoor and outdoor modelling of buildings from heterogeneous data. The heterogeneity is both in data type (image and Light Detection and Ranging (LiDAR)) and acquisition platform: terrestrial indoor/outdoor or aerial acquisition. The first issue of such modeling is thus to precisely register this data. The work carried out has confirmed that the environment and the type of data drive the choice of the registration algorithm. Our contribution consists in exploring the fundamental properties of the data and the acquisition platforms in order to propose potential solutions for all the registration problems encountered by the project. As in abuilding environment, most objects are composed of geometric primitives (planarpolygons, straight lines, openings), we chose to introduce registration algorithmsbased on these primitives. The basic idea of these algorithms consists in the definition of a global energy between the extracted primitives from the data-sets to register and the proposal of a robust method for optimizing this energy based on the RANSAC paradigm. Our contribution ranging from the proposal of robust methods to extract the selected primitives to the integration of these primitives in an efficient registration framework. Our solutions have exceeded the limitations of existing algorithms and have proven their effectiveness in solving the challenging problems encountered by the project such as the indoor/outdoor registration, image/LiDAR registration, and aerial/terrestrialregistration.