@article{670, abstract = {We propose an efficient method to model paper tearing in the context of interactive modeling. The method uses geometrical information to automatically detect potential starting points of tears. We further introduce a new hybrid geometrical and physical-based method to compute the trajectory of tears while procedurally synthesizing high resolution details of the tearing path using a texture based approach. The results obtained are compared with real paper and with previous studies on the expected geometric paths of paper that tears.}, author = {Schreck, Camille and Rohmer, Damien and Hahmann, Stefanie}, issn = {01677055}, journal = {Computer Graphics Forum}, number = {2}, pages = {95 -- 106}, publisher = {Wiley}, title = {{Interactive paper tearing}}, doi = {10.1111/cgf.13110}, volume = {36}, year = {2017}, } @article{1413, abstract = {This paper generalizes the well-known Diffusion Curves Images (DCI), which are composed of a set of Bezier curves with colors specified on either side. These colors are diffused as Laplace functions over the image domain, which results in smooth color gradients interrupted by the Bezier curves. Our new formulation allows for more color control away from the boundary, providing a similar expressive power as recent Bilaplace image models without introducing associated issues and computational costs. The new model is based on a special Laplace function blending and a new edge blur formulation. We demonstrate that given some user-defined boundary curves over an input raster image, fitting colors and edge blur from the image to the new model and subsequent editing and animation is equally convenient as with DCIs. Numerous examples and comparisons to DCIs are presented.}, author = {Jeschke, Stefan}, journal = {Computer Graphics Forum}, number = {2}, pages = {71 -- 79}, publisher = {Wiley-Blackwell}, title = {{Generalized diffusion curves: An improved vector representation for smooth-shaded images}}, doi = {10.1111/cgf.12812}, volume = {35}, year = {2016}, } @inproceedings{1630, abstract = {We present a method to learn and propagate shape placements in 2D polygonal scenes from a few examples provided by a user. The placement of a shape is modeled as an oriented bounding box. Simple geometric relationships between this bounding box and nearby scene polygons define a feature set for the placement. The feature sets of all example placements are then used to learn a probabilistic model over all possible placements and scenes. With this model, we can generate a new set of placements with similar geometric relationships in any given scene. We introduce extensions that enable propagation and generation of shapes in 3D scenes, as well as the application of a learned modeling session to large scenes without additional user interaction. These concepts allow us to generate complex scenes with thousands of objects with relatively little user interaction.}, author = {Guerrero, Paul and Jeschke, Stefan and Wimmer, Michael and Wonka, Peter}, location = {Los Angeles, CA, United States}, number = {4}, publisher = {ACM}, title = {{Learning shape placements by example}}, doi = {10.1145/2766933}, volume = {34}, year = {2015}, } @article{1814, abstract = {We present an efficient wavefront tracking algorithm for animating bodies of water that interact with their environment. Our contributions include: a novel wavefront tracking technique that enables dispersion, refraction, reflection, and diffraction in the same simulation; a unique multivalued function interpolation method that enables our simulations to elegantly sidestep the Nyquist limit; a dispersion approximation for efficiently amplifying the number of simulated waves by several orders of magnitude; and additional extensions that allow for time-dependent effects and interactive artistic editing of the resulting animation. Our contributions combine to give us multitudes more wave details than similar algorithms, while maintaining high frame rates and allowing close camera zooms.}, author = {Jeschke, Stefan and Wojtan, Christopher J}, journal = {ACM Transactions on Graphics}, number = {3}, publisher = {ACM}, title = {{Water wave animation via wavefront parameter interpolation}}, doi = {10.1145/2714572}, volume = {34}, year = {2015}, } @article{1906, abstract = {In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high-quality representation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and handles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since our preprocessing phase requires only a minor fraction of the whole data set at once, we provide maximum flexibility when dealing with growing data sets.}, author = {Arikan, Murat and Preiner, Reinhold and Scheiblauer, Claus and Jeschke, Stefan and Wimmer, Michael}, journal = {IEEE Transactions on Visualization and Computer Graphics}, number = {9}, pages = {1280 -- 1292}, publisher = {IEEE}, title = {{Large-scale point-cloud visualization through localized textured surface reconstruction}}, doi = {10.1109/TVCG.2014.2312011}, volume = {20}, year = {2014}, }