This work aims at developing a generic and anisotropic point error model, which is capable of computing magnitude and direction of a priori random errors, described in the form of error ellipsoids for each individual point of the cloud. The direct TLS observations are the range (ρ), vertical (α) and horizontal (θ) angles, each of which is in fact associated with a priori precision value. A practical methodology was designed and performed in real-world test environments to determine these precision values. The methodology has two experimental parts. The first part is a static and repetitive measurement configuration for the determination of a priori precisions of the vertical (σα) and horizontal (σθ) angles. The second part is the measurement of a test stand which contains four plates in white, light grey, dark grey and black colors, for the determination of a priori precisions of the range observations (σρ). The test stand measurement is performed in a recursive manner so that sensor-to-object distance, incidence angle and surface reflectivity are parameterized. The experiment was conducted with three TLSs, namely Faro Focus 3D X330, Riegl VZ400 and Z+F 5010x in the same location and atmospheric conditions. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. Validation of the proposed error model was performed in real world scenarios, which revealed feasibility of the model.
3D documentation and visualization of Cultural Heritage objects is an expanding application area. The selection of the
right technology for these kinds of applications is very important and strictly related to the project requirements, budget
and user's experience. Active sensors, i.e. triangulation based laser scanners and structured light systems are used for
many kinds of 3D object reconstruction tasks and in particular for 3D documentation of cultural heritage objects. This
study presents some experiences in the results of two case studies in which a close-range structured light system is used
for the 3D digitization. The paper includes all necessary steps of the 3D object modeling pipeline from data acquisition
to 3D visualization.
An algorithm for the least squares matching of overlapping 3D surfaces is presented. It estimates the transformation parameters between two or more fully 3D surfaces, using the Generalized Gauss-Markoff model, minimizing the sum of squares of the Euclidean distances between the surfaces. This formulation gives the opportunity of matching arbitrarily oriented 3D surfaces simultaneously, without using explicit tie points. Besides the mathematical model and execution aspects we give further extension of the basic model. The first extension is the simultaneous matching of sub-surface patches, which are selected in cooperative surface areas. It provides a computationally effective solution, since it matches only relevant multi-subpatches rather than the whole overlapping areas. The second extension is the matching of surface geometry and its attribute information, e.g. reflectance, color, temperature, etc., under a combined estimation model. We give practical examples for the demonstration of the basic method and the extensions.