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Item Interactive Modeling of Cellular Structures on Surfaces with Application to Additive Manufacturing(The Eurographics Association and John Wiley & Sons Ltd., 2020) Stadlbauer, Pascal; Mlakar, Daniel; Seidel, Hans-Peter; Steinberger, Markus; Zayer, Rhaleb; Panozzo, Daniele and Assarsson, UlfThe rich and evocative patterns of natural tessellations endow them with an unmistakable artistic appeal and structural properties which are echoed across design, production, and manufacturing. Unfortunately, interactive control of such patterns-as modeled by Voronoi diagrams, is limited to the simple two dimensional case and does not extend well to freeform surfaces. We present an approach for direct modeling and editing of such cellular structures on surface meshes. The overall modeling experience is driven by a set of editing primitives which are efficiently implemented on graphics hardware. We feature a novel application for 3D printing on modern support-free additive manufacturing platforms. Our method decomposes the input surface into a cellular skeletal structure which hosts a set of overlay shells. In this way, material saving can be channeled to the shells while structural stability is channeled to the skeleton. To accommodate the available printer build volume, the cellular structure can be further split into moderately sized parts. Together with shells, they can be conveniently packed to save on production time. The assembly of the printed parts is streamlined by a part numbering scheme which respects the geometric layout of the input model.Item SnakeBinning: Efficient Temporally Coherent Triangle Packing for Shading Streaming(The Eurographics Association and John Wiley & Sons Ltd., 2021) Hladky, Jozef; Seidel, Hans-Peter; Steinberger, Markus; Mitra, Niloy and Viola, IvanStreaming rendering, e.g., rendering in the cloud and streaming via a mobile connection, suffers from increased latency and unreliable connections. High quality framerate upsampling can hide these issues, especially when capturing shading into an atlas and transmitting it alongside geometric information. The captured shading information must consider triangle footprints and temporal stability to ensure efficient video encoding. Previous approaches only consider either temporal stability or sample distributions, but none focuses on both. With SnakeBinning, we present an efficient triangle packing approach that adjusts sample distributions and caters for temporal coherence. Using a multi-dimensional binning approach, we enforce tight packing among triangles while creating optimal sample distributions. Our binning is built on top of hardware supported real-time rendering where bins are mapped to individual pixels in a virtual framebuffer. Fragment shader interlock and atomic operations enforce global ordering of triangles within each bin, and thus temporal coherence according to the primitive order is achieved. Resampling the bin distribution guarantees high occupancy among all bins and a dense atlas packing. Shading samples are directly captured into the atlas using a rasterization pass, adjusting samples for perspective effects and creating a tight packing. Comparison to previous atlas packing approaches shows that our approach is faster than previous work and achieves the best sample distributions while maintaining temporal coherence. In this way, SnakeBinning achieves the highest rendering quality under equal atlas memory requirements. At the same time, its temporal coherence ensures that we require equal or less bandwidth than previous state-of-the-art. As SnakeBinning outperforms previous approach in all relevant aspects, it is the preferred choice for texture-based streaming rendering.Item Point-Pattern Synthesis using Gabor and Random Filters(The Eurographics Association and John Wiley & Sons Ltd., 2022) Huang, Xingchang; Memari, Pooran; Seidel, Hans-Peter; Singh, Gurprit; Ghosh, Abhijeet; Wei, Li-YiPoint pattern synthesis requires capturing both local and non-local correlations from a given exemplar. Recent works employ deep hierarchical representations from VGG-19 [SZ15] convolutional network to capture the features for both point-pattern and texture synthesis. In this work, we develop a simplified optimization pipeline that uses more traditional Gabor transform-based features. These features when convolved with simple random filters gives highly expressive feature maps. The resulting framework requires significantly less feature maps compared to VGG-19-based methods [TLH19; RGF*20], better captures both the local and non-local structures, does not require any specific data set training and can easily extend to handle multi-class and multi-attribute point patterns, e.g., disk and other element distributions. To validate our pipeline, we perform qualitative and quantitative analysis on a large variety of point patterns to demonstrate the effectiveness of our approach. Finally, to better understand the impact of random filters, we include a spectral analysis using filters with different frequency bandwidths.Item A Variational Loop Shrinking Analogy for Handle and Tunnel Detection and Reeb Graph Construction on Surfaces(The Eurographics Association and John Wiley & Sons Ltd., 2023) Weinrauch, Alexander; Mlakar, Daniel; Seidel, Hans-Peter; Steinberger, Markus; Zayer, Rhaleb; Myszkowski, Karol; Niessner, MatthiasThe humble loop shrinking property played a central role in the inception of modern topology but it has been eclipsed by more abstract algebraic formalisms. This is particularly true in the context of detecting relevant non-contractible loops on surfaces where elaborate homological and/or graph theoretical constructs are favored in algorithmic solutions. In this work, we devise a variational analogy to the loop shrinking property and show that it yields a simple, intuitive, yet powerful solution allowing a streamlined treatment of the problem of handle and tunnel loop detection. Our formalization tracks the evolution of a diffusion front randomly initiated on a single location on the surface. Capitalizing on a diffuse interface representation combined with a set of rules for concurrent front interactions, we develop a dynamic data structure for tracking the evolution on the surface encoded as a sparse matrix which serves for performing both diffusion numerics and loop detection and acts as the workhorse of our fully parallel implementation. The substantiated results suggest our approach outperforms state of the art and robustly copes with highly detailed geometric models. As a byproduct, our approach can be used to construct Reeb graphs by diffusion thus avoiding commonly encountered issues when using Morse functions.Item Subdivision-Specialized Linear Algebra Kernels for Static and Dynamic Mesh Connectivity on the GPU(The Eurographics Association and John Wiley & Sons Ltd., 2020) Mlakar, Daniel; Winter, Martin; Stadlbauer, Pascal; Seidel, Hans-Peter; Steinberger, Markus; Zayer, Rhaleb; Panozzo, Daniele and Assarsson, UlfSubdivision surfaces have become an invaluable asset in production environments. While progress over the last years has allowed the use of graphics hardware to meet performance demands during animation and rendering, high-performance is limited to immutable mesh connectivity scenarios. Motivated by recent progress in mesh data structures, we show how the complete Catmull-Clark subdivision scheme can be abstracted in the language of linear algebra. While this high-level formulation allows for a fully parallel implementation with significant performance gains, the underlying algebraic operations require further specialization for modern parallel hardware. Integrating domain knowledge about the mesh matrix data structure, we replace costly general linear algebra operations like matrix-matrix multiplication by specialized kernels. By further considering innate properties of Catmull-Clark subdivision, like the quad-only structure after refinement, we achieve an additional order of magnitude in performance and significantly reduce memory footprints. Our approach can be adapted seamlessly for different use cases, such as regular subdivision of dynamic meshes, fast evaluation for immutable topology and feature-adaptive subdivision for efficient rendering of animated models. In this way, patchwork solutions are avoided in favor of a streamlined solution with consistent performance gains throughout the production pipeline. The versatility of the sparse matrix linear algebra abstraction underlying our work is further demonstrated by extension to other schemes such as √3 and Loop subdivision.Item Eurographics 2023 - Final Report(2024-04-17) Seidel, Hans-PeterItem Cinematic Gaussians: Real-Time HDR Radiance Fields with Depth of Field(The Eurographics Association and John Wiley & Sons Ltd., 2024) Wang, Chao; Wolski, Krzysztof; Kerbl, Bernhard; Serrano, Ana; Bemama, Mojtaba; Seidel, Hans-Peter; Myszkowski, Karol; Leimkühler, Thomas; Chen, Renjie; Ritschel, Tobias; Whiting, EmilyRadiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes in low dynamic range (LDR), which restricts their use to evenly lit environments and hinders immersive viewing experiences. Secondly, their reliance on a pinhole camera model, assuming all scene elements are in focus in the input images, presents practical challenges and complicates refocusing during novel-view synthesis. Addressing these limitations, we present a lightweight method based on 3D Gaussian Splatting that utilizes multi-view LDR images of a scene with varying exposure times, apertures, and focus distances as input to reconstruct a high-dynamic-range (HDR) radiance field. By incorporating analytical convolutions of Gaussians based on a thin-lens camera model as well as a tonemapping module, our reconstructions enable the rendering of HDR content with flexible refocusing capabilities. We demonstrate that our combined treatment of HDR and depth of field facilitates real-time cinematic rendering, outperforming the state of the art.Item Video Frame Interpolation for High Dynamic Range Sequences Captured with Dual-exposure Sensors(The Eurographics Association and John Wiley & Sons Ltd., 2023) Cogalan, Ugur; Bemana, Mojtaba; Seidel, Hans-Peter; Myszkowski, Karol; Myszkowski, Karol; Niessner, MatthiasVideo frame interpolation (VFI) enables many important applications such as slow motion playback and frame rate conversion. However, one major challenge in using VFI is accurately handling high dynamic range (HDR) scenes with complex motion. To this end, we explore the possible advantages of dual-exposure sensors that readily provide sharp short and blurry long exposures that are spatially registered and whose ends are temporally aligned. This way, motion blur registers temporally continuous information on the scene motion that, combined with the sharp reference, enables more precise motion sampling within a single camera shot. We demonstrate that this facilitates a more complex motion reconstruction in the VFI task, as well as HDR frame reconstruction that so far has been considered only for the originally captured frames, not in-between interpolated frames. We design a neural network trained in these tasks that clearly outperforms existing solutions. We also propose a metric for scene motion complexity that provides important insights into the performance of VFI methods at test time.Item Eurographics Medal 2024 -- Report to ExC_EG2024(2024-04-17) Seidel, Hans-PeterItem Enhancing Image Quality Prediction with Self-supervised Visual Masking(The Eurographics Association and John Wiley & Sons Ltd., 2024) Çogalan, Ugur; Bemana, Mojtaba; Seidel, Hans-Peter; Myszkowski, Karol; Bermano, Amit H.; Kalogerakis, EvangelosFull-reference image quality metrics (FR-IQMs) aim to measure the visual differences between a pair of reference and distorted images, with the goal of accurately predicting human judgments. However, existing FR-IQMs, including traditional ones like PSNR and SSIM and even perceptual ones such as HDR-VDP, LPIPS, and DISTS, still fall short in capturing the complexities and nuances of human perception. In this work, rather than devising a novel IQM model, we seek to improve upon the perceptual quality of existing FR-IQM methods. We achieve this by considering visual masking, an important characteristic of the human visual system that changes its sensitivity to distortions as a function of local image content. Specifically, for a given FR-IQM metric, we propose to predict a visual masking model that modulates reference and distorted images in a way that penalizes the visual errors based on their visibility. Since the ground truth visual masks are difficult to obtain, we demonstrate how they can be derived in a self-supervised manner solely based on mean opinion scores (MOS) collected from an FR-IQM dataset. Our approach results in enhanced FR-IQM metrics that are more in line with human prediction both visually and quantitatively.