Devrim Akca

Co-registration of Surfaces by 3D Least Squares Matching

A method for the automatic co-registration of 3D surfaces is presented. The method utilizes the mathematical model of Least Squares 2D image matching and extends it for solving the 3D surface matching problem. The transformation parameters of the search surfaces are estimated with respect to a template surface. The solution is achieved when the sum of the squares of the 3D spatial (Euclidean) distances between the surfaces are minimized. The parameter estimation is achieved using the Generalized Gauss-Markov model. Execution level implementation details are given. Apart from the co-registration of the point clouds generated from spaceborne, airborne and terrestrial sensors and techniques, the proposed method is also useful for change detection, 3D comparison, and quality assessment tasks. Experiments using terrain data examples show the capabilities of the method.

Performance evaluation of a coded structured light system for cultural heritage applications

D 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 users 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.

A flexible mathematical model for matching of 3D surfaces and attributes

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.

A generic point error model for TLS derived point clouds

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.

Calibration and accuracy testiing of mobile phone cameras

This paper examines the potential of mobile phones to be used as a front-end sensor for photogrammetric procedures and applications. For this purpose we are currently calibrating various mobile phones over our indoor 3D testfield, using self-calibration. Using the same testfield we are performing accuracy tests in order to evaluate the metric performance. This paper reports about first experiences in calibration and accuracy validation of mobile phone cameras.