Patrick Degener

Image-based registration of 3D-range data using feature surface elements

Digitizing real-life objects via range scanners, stereo vision or tactile sensors usually requires the composition of multiple range images. In this paper we exploit intensity images often recorded with the range data and propose a fully automatic registration technique using 2D-image features with intrinsic scale information for finding corresponding points on the 3D-views. In our approach, the fine registration of two range images is performed by first aligning the feature points themselves, followed by a so-called constrained-domain alignment step. In the latter, rather than feature points, we consider feature surface elements that are derived using the scale information inherently established with the 2D-features. The global registration error is minimized using graph relaxation techniques to mediate the transformations required to align the multiple range images. We demonstrate the power and feasibility of our method by a case-study in the cultural heritage domain.

Context Aware Terrain Visualization for Wayfinding and Navigation

To assist wayfinding and navigation, the display of maps and driving directions on mobile devices is nowadays commonplace. While existing system can naturally exploit GPS information to facilitate orientation, the inherently limited screen space is often perceived as a drawback compared to traditional street maps as it constrains the perception of contextual information. Moreover, occlusion issues add to this problem if the environment is shown from the popular egocentric perspective.

A variational approach for automatic generation of panoramic maps

Panoramic maps combine the advantages of both ordinary geographic maps and terrestrial images. While inheriting the familiar perspective of terrestrial images, they provide a good overview and avoid occlusion of important geographical features. The designer achieves this by skillful choice and integration of several views in a single image. As important features on the surface must be carefully rearranged to guarantee their visibility, the manual design of panoramic maps requires many hours of tedious and painstaking work. In this article we take a variational approach to the design of panoramic maps. Starting from conventional elevation data and aerial images, our method fully automatically computes panoramic maps from arbitrary viewpoints. It rearranges geographic structures to maximize the visibility of a specified set of features while minimizing the deformation of the landscapes shape.

Effective Visualization of Short Routes

In this work we develop a new alternative to conventional maps for visualization of relatively short paths as they are frequently encountered in hotels, resorts or museums. Our approach is based on a warped rendering of a 3D model of the environment such that the visualized path appears to be straight even though it may contain several junctions. This has the advantage that the beholder of the image gains a realistic impression of the surroundings along the way which makes it easy to retrace the route in practice. We give an intuitive method for generation of such images and present results from user studies undertaken to evaluate the benefit of the warped images for orientation in unknown environments.

Simple and Efficient Mesh Editing with Consistent Local Frames

Mesh editing methods based on differential surface representations are known for their efficiency and ease of implementation. For reconstruction from such representations, local frames have to be determined which is a nonlinear problem. In linear approximations frames can either degenerate or become inconsistent with the geometry. Both results in contra-intuitive deformations. Existing nonlinear approaches, however, are comparatively slow and considerably more complex. In this paper we present a differential representation that implicitly enforces orthogonal and geometry consistent frames while allowing a simple and efficient implementation. In particular, it enforces conformal surface deformations preserving local texture features.This paper presents a novel integrative information visualization framework for cross-subject neuroimaging data analysis. The framework can integrate multimodal information captured by different imaging modalities and population-based statistical information presented by different subjects. In this framework, accurate registration of cortical structures is the foundation for the information integration across population. We present a non-rigid intersubject brain surface registration method using conformal structure and spherical thin-plate splines. Spherical thin-plate splines are designed to explicitly match prominent homologous landmarks, and meanwhile, interpolate a global deformation field on the spherical domain, registering brain surfaces in a transformed space. Subsequently, an approach for the integrative information fusion and visualization is presented to handle multimodality neuroimaging data. The entire framework demonstrates its usefulness in multimodality neuroimaging data analysis across subjects.

Texture Atlas Generation for Inconsistent Meshes and Point Sets

In order to compute texture atlases with low stretch and hardly visible texture seams existing texture mapping tools pose high demands on the quality of surface representations like consistent orientation, watertightness, or manifoldness which many models commonly used in day-to-day modeling practice fail to meet. In this paper we propose an approach that bridges the gap between requirements of high quality texture mapping tools and poor mesh connectivity of models used in practice. In the spirit of classical two-part mapping an intermediate proxy surface is created that can be processed by high quality texture mapping tools. The texture signal is transferred to the original geometry using a novel mapping technique. Avoiding a modification of the original geometry typical problems of mesh repairing approaches like approximation errors or feature corruption are circumvented. As our method poses almost no demands on connectivity it can also be applied to point clouds. Contrary to classical two- part mapping, the method requires little user-interaction. Its robustness and quality are demonstrated in several examples.