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Item Interactive Projective Texturing for Non-Photorealistic Shading of Technical 3D Models(The Eurographics Association, 2013) Lux, Roland; Trapp, Matthias; Semmo, Amir; Döllner, Jürgen; Silvester Czanner and Wen TangThis paper presents a novel interactive rendering technique for creating and editing shadings for man-made objects in technical 3D visualizations. In contrast to shading approaches that use intensities computed based on surface normals (e.g., Phong, Gooch, Toon shading), the presented approach uses one-dimensional gradient textures, which can be parametrized and interactively manipulated based on per-object bounding volume approximations. The fully hardware-accelerated rendering technique is based on projective texture mapping and customizable intensity transfer functions. A provided performance evaluation shows comparable results to traditional normal-based shading approaches. The work also introduce simple direct-manipulation metaphors that enables interactive user control of the gradient texture alignment and intensity transfer functions.Item Natural Phenomena as Metaphors for Visualization of Trend Data in Interactive Software Maps(The Eurographics Association, 2015) Würfel, Hannes; Trapp, Matthias; Limberger, Daniel; Döllner, Jürgen; Rita Borgo and Cagatay TurkaySoftware maps are a commonly used tool for code quality monitoring in software-development projects and decision making processes. While providing an important visualization technique for the hierarchical system structure of a single software revision, they lack capabilities with respect to the visualization of changes over multiple revisions. This paper presents a novel technique for visualizing the evolution of the software system structure based on software metric trends. These trend maps extend software maps by using real-time rendering techniques for natural phenomena yielding additional visual variables that can be effectively used for the communication of changes. Therefore, trend data is automatically computed by hierarchically aggregating software metrics. We demonstrate and discuss the presented technique using two real world data sets of complex software systems.Item Multi-Perspective Detail+Overview Visualization for 3D Building Exploration(The Eurographics Association, 2013) Pasewaldt, Sebastian; Trapp, Matthias; Döllner, Jürgen; Silvester Czanner and Wen TangVirtual 3D building models, as key elements of virtual 3D city models, are used in a growing number of application domains, such as geoanalysis, disaster management and architectural planning. Visualization systems for such building models often rely on perspective or orthogonal projections using a single viewpoint. Therefore, the exploration of a complete model requires a user to change the viewpoint multiple times and to memorize the content of each view to obtain a comprehensive mental model. Since this is usually a time-consuming task, which implies context switching, current visualization systems use multiple viewports to simultaneously depict an object from different perspectives. Our approach extends the idea of multiple viewports by combining two linked views for the interactive exploration of virtual 3D buildings model and their façades. In contrast to traditional approaches, we automatically generate a multi-perspective view that simultaneously depicts all façades of the building in one overview image. This facilitates the process of obtaining overviews and supports fast and direct navigation to various points-of-interest. We describe the concept and implementations of our Multiple-Center-of-Projection camera model for real-time multi-perspective image synthesis. Further, we provide insights into different interaction techniques for linked multi-perspective views and outline approaches of future work.Item Assessing the Reliability of Integrated Gradients-Based Saliency Maps for 3D Point Cloud Semantic Segmentation Models(The Eurographics Association, 2024) Ciprián-Sánchez, Jorge F.; Burmeister, Josafat-Mattias; Cech, Tim; Richter, Rico; Döllner, Jürgen; Hunter, David; Slingsby, AidanDeep learning models achieve high accuracy in the semantic segmentation of 3D point clouds; however, it is challenging to discern which patterns a model has learned and how it derives its output from the input. Recently, the Integrated Gradients method has been adopted to explain semantic segmentation models for 3D point clouds. This method can be used to generate saliency maps that visualize the contribution of input points to a particular model output. However, there is a lack of quantitative evaluation of the reliability of the generated saliency maps and the influence of the baseline selection (a central component of Integrated Gradients) on the method's results. In this paper, we quantitatively evaluate the reliability of saliency maps generated by the Integrated Gradients method for a 3D point cloud semantic segmentation model through well-known sanity checks from the image domain that we adapt to 3D point cloud segmentation. We perform these sanity checks for three different baselines to further evaluate the stability of the generated saliency maps concerning the baseline choice. Our results indicate that the Integrated Gradients method is sensitive to both the parameters of the model and training labels, unstable concerning the choice of baseline, and that, although it can identify points with high contributions to the model output, it fails to identify correctly if such contributions are positive or negative. Finally, we propose an averaging approach to aggregate the results of points that receive multiple scores from Integrated Gradients during the segmentation process and show that it produces saliency maps that better reflect high-contribution input points than previous approaches.Item Interactive GPU-based Image Deformation for Mobile Devices(The Eurographics Association, 2016) Vollmer, Jan Ole; Trapp, Matthias; Döllner, Jürgen; Cagatay Turkay and Tao Ruan WanInteractive image deformation is an important feature of modern image processing pipelines. It is often used to create caricatures and animation for input images, especially photos. State-of-the-art image deformation techniques are based on transforming vertices of a mesh, which is textured by the input image, using affine transformations such as translation, and scaling. However, the resulting visual quality of the output image depends on the geometric resolution of the mesh. Performing these transformations on the CPU often further inhibits performance and quality. This is especially problematic on mobile devices where the limited computational power reduces the maximum achievable quality. To overcome these issue, we propose the concept of an intermediate deformation buffer that stores deformation information at a resolution independent of the mesh resolution. This allows the combination of a high-resolution buffer with a low-resolution mesh for interactive preview, as well as a high-resolution mesh to export the final image. Further, we present a fully GPU-based implementation of this concept, taking advantage of modern OpenGL ES features, such as compute shaders.Item Exploring High-Dimensional Data by Pointwise Filtering of Low-Dimensional Embeddings(The Eurographics Association, 2024) Atzberger, Daniel; Jobst, Adrian; Scheibel, Willy; Döllner, Jürgen; Hunter, David; Slingsby, AidanDimensionality reductions are a class of unsupervised learning algorithms that aim to find a lower-dimensional embedding for a high-dimensional dataset while preserving local and global structures. By representing a high-dimensional dataset as a twodimensional scatterplot, a user can explore structures within the dataset. However, dimensionality reductions inherit distortions that might result in false deductions. This work presents a visualization approach that combines a two-dimensional scatterplot derived from a dimensionality reduction with two pointwise filtering possibilities. Each point is associated with two pointwise metrics that quantify the correctness of its neighborhood and similarity to surrounding data points. By setting threshold for these two metrics, the user is supported in several scatterplot analytics tasks, e.g., class separation and outlier detection. We apply our visualization to a text corpus to detect interesting data points visually and discuss the findings.