Web-based scientific exploration and analysis of 3D scanned cuneiform datasets for collaborative research

The three-dimensional cuneiform script is one of the oldest known writing systems and a central object of research in Ancient Near Eastern Studies and Hittitology. An important step towards the understanding of the cuneiform script is the provision of opportunities and tools for joint analysis. This paper presents an approach that contributes to this challenge: a collaborative compatible web-based scientific exploration and analysis of 3D scanned cuneiform fragments. The WebGL -based concept incorporates methods for compressed web-based content delivery of large 3D datasets and high quality visualization. To maximize accessibility and to promote acceptance of 3D techniques in the field of Hittitology, the introduced concept is integrated into the Hethitologie-Portal Mainz, an established leading online research resource in the field of Hittitology, which until now exclusively included 2D content. The paper shows that increasing the availability of 3D scanned archaeological data through a web-based interface can provide significant scientific value while at the same time finding a trade-off between copyright induced restrictions and scientific usability

Contributions to computer-aided analysis of cuneiform tablet fragments

This thesis presents methods for computer-aided three-dimensional analysis of digitized cuneiform tablets, an ancient type of writing documents. Since cuneiform script is predominantly conserved in the form of fractured clay tablet fragments, identifying matching fragments is a central task of manuscript reconstruction. This goal can benefit from the increasing 3D digitization of cuneiform fragments, which offers access to highly accurate cuneiform representations. The main contribution of the thesis is a novel model-based method for the extraction of individual cuneiform wedges and associated wedge geometries from 3D scans, which can serve as a base for a statistical analysis of script features. This new automated approach enables access to large amounts of accurate quantitative cuneiform script features, which were not accessible by previously available 2D methods and can be employed for script similarity-based identification of candidates for fragment joining. A central aspect and challenging task is the robustness of the presented extraction method against scanning issues and mesh errors. This is achieved by employing a watershed-based wedge area extraction operating on a surface distance field with a subsequent constructive multi-stage model fitting. The extracted wedge models are refined by a wedge type classification followed by an effective wedge validation to handle false detections on fracture faces and damaged surfaces. An evaluation with respect to extraction rates, robustness, and performance shows the suitability of the developed methods that goes beyond an application purely for cuneiform fragment joining. To address some compromises made during the wedge extraction regarding the representation of complex features, a fast supplementary approach for extracting skeletal surface features is presented. These features provide an alternative readable cuneiform representation and are created using a thinning approach on an approximated distance field. The quality of the resulting skeletons is optimized by employing a complex junction resolution, branch pruning and branch simplification methods, where both pruning and simplification can be used to adjust the resulting representation to different use cases. Aside from manual feature analysis, possible application scenarios also include providing a representation that can be handled by GraphCNNs for retrieval related tasks on cuneiform structures. The cuneiform segmentation methods are complemented by a set of visualization concepts for a cuneiform segmentation framework. This includes a hierarchical concept for data handling and persistent storage of the generated segmentation data. Beyond, methods for fast rendering of large meshes, visualization methods to achieve good depth perception, detail enhancement, and semi-realistic surface shading are integrated. In order to not only address application scenarios like fragment joining and collation related tasks, the framework provides a sophisticated, highly interactive, and flexible segmentation data visualization that additionally offers fast geometry selection methods. A good accessibility of the generated data is guaranteed though an XML-based file format for storing segmentation data and through providing flexible data export methods. Although the framework is primarily intended for real-time segmentation, most segmentation methods can also be scheduled to process large numbers of fragments without user interaction. All presented methods are evaluated with respect to performance aspects and their suitability for a set of philological use cases. The developed methods can be used flexibly in the scope of many aspects of the investigated application cases. This does not only apply to the automated feature extraction, but also to manual analysis aspects, which were discovered only by the new availability of the methods. The usability of the framework is underlined by the fact that it is actively being used by philologists from the Hethitologie-Portal Mainz, an established online resource in Hittitology

Learning in a high dimensional space: Fast omnidirectional quadrupedal locomotion

Abstract. This paper presents an efficient way to learn fast omnidirectional quadrupedal walking gaits. We show that the common approaches to control the legs can be further improved by allowing more degrees of freedom in the trajectory generation for the legs. To achieve good omnidirectional movements, we suggest to use different parameters for different walk requests and interpolate between them. The approach has been implemented for the Sony Aibo and used by the GermanTeam in the Four-Legged-League in 2005. A standard learning strategy has been adopted, so that the optimization process of a parameter set can be done within one hour, without human intervention. The resulting walk achieved remarkable speeds, both in pure forward walking and in omnidirectional movements.

Web-Based scientific exploration and analysis of 3D scanned cuneiform datasets for collaborative research

The three-dimensional cuneiform script is one of the oldest known writing systems and a central object of research in Ancient Near Eastern Studies and Hittitology. An important step towards the understanding of the cuneiform script is the provision of opportunities and tools for joint analysis. This paper presents an approach that contributes to this challenge: a collaborative compatible web-based scientific exploration and analysis of 3D scanned cuneiform fragments. The WebGL -based concept incorporates methods for compressed web-based content delivery of large 3D datasets and high quality visualization. To maximize accessibility and to promote acceptance of 3D techniques in the field of Hittitology, the introduced concept is integrated into the Hethitologie-Portal Mainz, an established leading online research resource in the field of Hittitology, which until now exclusively included 2D content. The paper shows that increasing the availability of 3D scanned archaeological data through a web-based interface can provide significant scientific value while at the same time finding a trade-off between copyright induced restrictions and scientific usability

Learning Fast Walking Patterns with Reliable Odometry Information for Four-Legged Robots

In this paper we describe a way to control and learn walking patters for a four-legged robot which result in very fast and stable omnidirectional walks with accurate odometry information. The fastest forward walk which was learned on a Sony Aibo ERS 7 with this approach reaches more than 50 cm/s. This is more than 25 % faster than the fastest published walk found by any RoboCup team so far. The fast and manoeuvrable walk contributed a lot to the good overall performance of our team and helped to win all attended RoboCup competitions in 2005. I

Analysis of the Accuracy and Robustness of the Leap Motion Controller

The Leap Motion Controller is a new device for hand gesture controlled user interfaces with declared sub-millimeter accuracy. However, up to this point its capabilities in real environments have not been analyzed. Therefore, this paper presents a first study of a Leap Motion Controller. The main focus of attention is on the evaluation of the accuracy and repeatability. For an appropriate evaluation, a novel experimental setup was developed making use of an industrial robot with a reference pen allowing a position accuracy of 0.2 mm. Thereby, a deviation between a desired 3D position and the average measured positions below 0.2mmhas been obtained for static setups and of 1.2mmfor dynamic setups. Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction

Simulation of intra-aneurysmal blood flow by different numerical methods

The occlusional performance of sole endoluminal stenting of intracranial aneurysms is controversially discussed in the literature. Simulation of blood flow has been studied to shed light on possible causal attributions. The outcome, however, largely depends on the numerical method and various free parameters. The present study is therefore conducted to find ways to define parameters and efficiently explore the huge parameter space with finite element methods (FEMs) and lattice Boltzmann methods (LBMs). The goal is to identify both the impact of different parameters on the results of computational fluid dynamics (CFD) and their advantages and disadvantages. CFD is applied to assess flow and aneurysmal vorticity in 2D and 3D models. To assess and compare initial simulation results, simplified 2D and 3D models based on key features of real geometries and medical expert knowledge were used. A result obtained from this analysis indicates that a combined use of the different numerical methods, LBM for fast exploration and FEM for a more in-depth look, may result in a better understanding of blood flow and may also lead to more accurate information about factors that influence conditions for stenting of intracranial aneurysms