טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentAbu Nassar Elia
SubjectRegistration of Terrestrial Laser Scans in Environments
without Conspicuous Entities
DepartmentDepartment of Civil and Environmental Engineering
Supervisor Professor Sagi Filin
Full Thesis textFull thesis text - English Version


Abstract

Registration of individual scans into a common reference frame is fundamental processing stage. For scans of man-made scenes, registration benefits from the relatively simple geometric shapes that may be easily detected in the data. Studies have made use of well-defined features, e.g., points, lines, or planes, or utilized additional data sources such as color and intensity data, which relate to the object radiometry. Suitable as they are for urban scenes, such approaches are inapplicable for alignment of natural environment scans, which are characterized by natural, undefined forms, geometrical continuity and albedo homogeneity.


This thesis proposes a new methodology for registration of terrestrial laser scans of natural scenes with no prior positional information. The proposed approach involves curvature-based descriptors for key-feature extraction. Analysis of common curvature parameters have shown their unsuitability for finding relevant features in characteristic scans. Thus, transition zones between concave and convex areas were developed here as key-features for the registration. Contrasting saliencies, such curves always exist and form reliable features for registration. The proposed approach is capable of registering point-clouds with variable densities, partial overlap and occluded areas. It is also efficient in finding key-features in monotonous areas and ones characterized by lack of dominant entities. Experiments show registration accuracy of a few centimeters that is comparable to results of manual registration, while exhibiting high robustness to natural-scene complexity. Such level of accuracy enables the next stage of mutual-alignment refinement using iterative methods.