Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds

Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larger rotational convergence region than the existing methods, e.g., the Iterative Closest Point (ICP)

Computer Vision and Graphics for Heritage Preservation and Digital Archaeology

The goal of this work is to provide attendees with a survey of topics related to Heritage Preservation and Digital Archeology, which are challenging and motivating subjects to both computer vision and graphics community. These issues have been gaining increasing attention and priority within the scientific scenario and among funding agencies and development organizations over the last years. Motivations to this work are the recent efforts in the digital preservation of cultural heritage objects and sites before degradation or damage caused by environmental factors or human development. One of the main focuses of these researches is the development of new techniques for realistic 3D model building from images, preserving as much information as possible. We intend to introduce and discuss several emerging topics in computer vision and graphics related to the proposed theme while highlighting the major contributions and advances in these fields

Multimodal Three Dimensional Scene Reconstruction, The Gaussian Fields Framework

The focus of this research is on building 3D representations of real world scenes and objects using different imaging sensors. Primarily range acquisition devices (such as laser scanners and stereo systems) that allow the recovery of 3D geometry, and multi-spectral image sequences including visual and thermal IR images that provide additional scene characteristics. The crucial technical challenge that we addressed is the automatic point-sets registration task. In this context our main contribution is the development of an optimization-based method at the core of which lies a unified criterion that solves simultaneously for the dense point correspondence and transformation recovery problems. The new criterion has a straightforward expression in terms of the datasets and the alignment parameters and was used primarily for 3D rigid registration of point-sets. However it proved also useful for feature-based multimodal image alignment. We derived our method from simple Boolean matching principles by approximation and relaxation. One of the main advantages of the proposed approach, as compared to the widely used class of Iterative Closest Point (ICP) algorithms, is convexity in the neighborhood of the registration parameters and continuous differentiability, allowing for the use of standard gradient-based optimization techniques. Physically the criterion is interpreted in terms of a Gaussian Force Field exerted by one point-set on the other. Such formulation proved useful for controlling and increasing the region of convergence, and hence allowing for more autonomy in correspondence tasks. Furthermore, the criterion can be computed with linear complexity using recently developed Fast Gauss Transform numerical techniques. In addition, we also introduced a new local feature descriptor that was derived from visual saliency principles and which enhanced significantly the performance of the registration algorithm. The resulting technique was subjected to a thorough experimental analysis that highlighted its strength and showed its limitations. Our current applications are in the field of 3D modeling for inspection, surveillance, and biometrics. However, since this matching framework can be applied to any type of data, that can be represented as N-dimensional point-sets, the scope of the method is shown to reach many more pattern analysis applications

Evaluating the Use of Lidar for Landslide Monitoring on Oklahoma Highways

Landslides cause huge human loss and property damage when they occur near infrastructure such as highways. The current approach for dealing with landslides by the Oklahoma Department of Transportation (ODOT) is primarily reactive because there is no effective monitoring mechanism to assess the risk of landslide properly. When the damage is already done, expensive repairs follows because the repair process is time driven and the use of resources may not be the most cost-effective. Traffic lane closures during the repair increases travel time and road users’ cost. This gives an opportunity to look for alternative practices. Several studies have proved that the LIDAR technology can be used to detect the slope changes in mountains, but there is no readily available generalized framework to apply this technology to monitor or assess the risk of landslides. The objectives of this study are 1) to develop a comprehensive workflow to apply this technology, 2) to evaluate registration and vegetation algorithms on the collected data, 3) to assess the displacement change over various seasons, and 4) to assess the impact of vegetation removal and downsampling algorithms on displacement change. For this study, the data was collected from four different sites that include both rock type and soil type slopes on Oklahoma highways, collected in four different seasons (summer, dry, winter and warm seasons) of the year. Then, M3C2 displacement analysis was performed on different seasons’ data to identify the displacement change over different seasons. Throughout the entire research process, various technical challenges associated with the application of the LIDAR technology were reported along with recommendations to overcome these challenges. Through M3C2 analysis, it was observed that the largest change was observed during June and September. By considering the current level of registration, no significant change was observed in the majority of the areas. It was also observed from the study that vegetation removal and downsampling have impacts on the result of statistical displacement and significant change analyses. The comprehensive workflow developed in this study can help ODOT to implement the LIDAR technology to monitor and assess the risk of landslides on highways in a cost effective manner.Civil Engineerin

Methods for 3D Geometry Processing in the Cultural Heritage Domain

This thesis presents methods for 3D geometry processing under the aspects of cultural heritage applications. After a short overview over the relevant basics in 3D geometry processing, the present thesis investigates the digital acquisition of 3D models. A particular challenge in this context are on the one hand difficult surface or material properties of the model to be captured. On the other hand, the fully automatic reconstruction of models even with suitable surface properties that can be captured with Laser range scanners is not yet completely solved. This thesis presents two approaches to tackle these challenges. One exploits a thorough capture of the object’s appearance and a coarse reconstruction for a concise and realistic object representation even for objects with problematic surface properties like reflectivity and transparency. The other method concentrates on digitisation via Laser-range scanners and exploits 2D colour images that are typically recorded with the range images for a fully automatic registration technique. After reconstruction, the captured models are often still incomplete, exhibit holes and/or regions of insufficient sampling. In addition to that, holes are often deliberately introduced into a registered model to remove some undesired or defective surface part. In order to produce a visually appealing model, for instance for visualisation purposes, for prototype or replica production, these holes have to be detected and filled. Although completion is a well-established research field in 2D image processing and many approaches do exist for image completion, surface completion in 3D is a fairly new field of research. This thesis presents a hierarchical completion approach that employs and extends successful exemplar-based 2D image processing approaches to 3D and fills in detail-equipped surface patches into missing surface regions. In order to identify and construct suitable surface patches, selfsimilarity and coherence properties of the surface context of the hole are exploited. In addition to the reconstruction and repair, the present thesis also investigates methods for a modification of captured models via interactive modelling. In this context, modelling is regarded as a creative process, for instance for animation purposes. On the other hand, it is also demonstrated how this creative process can be used to introduce human expertise into the otherwise automatic completion process. This way, reconstructions are feasible even of objects where already the data source, the object itself, is incomplete due to corrosion, demolition, or decay.Methoden zur 3D-Geometrieverarbeitung im Kulturerbesektor In dieser Arbeit werden Methoden zur Bearbeitung von digitaler 3D-Geometrie unter besonderer Berücksichtigung des Anwendungsbereichs im Kulturerbesektor vorgestellt. Nach einem kurzen Überblick über die relevanten Grundlagen der dreidimensionalen Geometriebehandlung wird zunächst die digitale Akquise von dreidimensionalen Objekten untersucht. Eine besondere Herausforderung stellen bei der Erfassung einerseits ungünstige Oberflächen- oder Materialeigenschaften der Objekte dar (wie z.B. Reflexivität oder Transparenz), andererseits ist auch die vollautomatische Rekonstruktion von solchen Modellen, die sich verhältnismäßig problemlos mit Laser-Range Scannern erfassen lassen, immer noch nicht vollständig gelöst. Daher bilden zwei neuartige Verfahren, die diesen Herausforderungen begegnen, den Anfang. Auch nach der Registrierung sind die erfassten Datensätze in vielen Fällen unvollständig, weisen Löcher oder nicht ausreichend abgetastete Regionen auf. Darüber hinaus werden in vielen Anwendungen auch, z.B. durch Entfernen unerwünschter Oberflächenregionen, Löcher gewollt hinzugefügt. Für eine optisch ansprechende Rekonstruktion, vor allem zu Visualisierungszwecken, im Bildungs- oder Unterhaltungssektor oder zur Prototyp- und Replik-Erzeugung müssen diese Löcher zunächst automatisch detektiert und anschließend geschlossen werden. Obwohl dies im zweidimensionalen Fall der Bildbearbeitung bereits ein gut untersuchtes Forschungsfeld darstellt und vielfältige Ansätze zur automatischen Bildvervollständigung existieren, ist die Lage im dreidimensionalen Fall anders, und die Übertragung von zweidimensionalen Ansätzen in den 3D stellt vielfach eine große Herausforderung dar, die bislang keine zufriedenstellenden Lösungen erlaubt hat. Nichtsdestoweniger wird in dieser Arbeit ein hierarchisches Verfahren vorgestellt, das beispielbasierte Konzepte aus dem 2D aufgreift und Löcher in Oberflächen im 3D unter Ausnutzung von Selbstähnlichkeiten und Kohärenzeigenschaften des Oberflächenkontextes schließt. Um plausible Oberflächen zu erzeugen werden die Löcher dabei nicht nur glatt gefüllt, sondern auch feinere Details aus dem Kontext rekonstruiert. Abschließend untersucht die vorliegende Arbeit noch die Modifikation der vervollständigten Objekte durch Freiformmodellierung. Dies wird dabei zum einen als kreativer Prozess z.B. zu Animationszwecken betrachtet. Zum anderen wird aber auch untersucht, wie dieser kreative Prozess benutzt werden kann, um etwaig vorhandenes Expertenwissen in die ansonsten automatische Vervollständigung mit einfließen zu lassen. Auf diese Weise werden auch Rekonstruktionen ermöglicht von Objekten, bei denen schon die Datenquelle, also das Objekt selbst z.B. durch Korrosion oder mutwillige Zerstörung unvollständig ist