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Chair of Visual Computing
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Informatik

Chair of Visual Computing

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  • Research
    • Rendering and Visualization
    • Geometric Modeling and 3D Reconstruction
    • Virtual, Mixed, and Augmented Reality
    • Visual Computing for Digital Humanities and Social Sciences
    • Visual Healthcare Computing
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    • Vertiefungsrichtung Visual Computing
    • Summer Term 2025
    • Winter Term 2024/25
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  2. Publications
  3. Multi-Resolution Attributes for Hardware Tessellated Objects

Multi-Resolution Attributes for Hardware Tessellated Objects

In page navigation: Publications
  • Adaptive stray-light compensation in dynamic multi-projection mapping
  • Adaptive Temporal Sampling for Volumetric Path Tracing of Medical Data
  • Analytic Displacement Mapping using Hardware Tessellation
  • Anisotropic Surface Based Deformation
  • Auto-Calibration for Dynamic Multi-Projection Mapping on Arbitrary Surfaces
  • Automated Heart Localization in Cardiac Cine MR Data
  • Demo of Face2Face: Real-time Face Capture and Reenactment of RGB Videos
  • Enhanced Sphere Tracing
  • Evaluating the Usability of Recent Consumer-Grade 3D Input Devices
  • Face2Face: Real-time Face Capture and Reenactment of RGB Videos
  • FaceForge: Markerless Non-Rigid Face Multi-Projection Mapping
  • FaceInCar: Real-time Dense Monocular Face Tracking of a Driver
  • FaceVR: Real-Time Facial Reenactment and Eye Gaze Control in Virtual Reality
  • GroPBS: Fast Solver for Implicit Electrostatics of Biomolecules
  • Grundsätzliche Überlegungen zur Edition des Bestandes an Münzen der FAU als frei zugängliche Datenbank im WWW
  • HeadOn: Real-time Reenactment of Human Portrait Videos
  • Hierarchical Multi-Layer Screen-Space Ray Tracing
  • Hybrid Mono-Stereo Rendering in Virtual Reality
  • Interactive Model-based Reconstruction of the Human Head using an RGB-D Sensor
  • Interactive Painting and Lighting in Dynamic Multi-Projection Mapping
  • Learning Real-Time Ambient Occlusion from Distance Representations
  • Low-Cost Real-Time 3D Reconstruction of Large-Scale Excavation Sites using an RGB-D Camera
  • Multi-Layer Depth of Field Rendering with Tiled Splatting
  • Multi-Resolution Attributes for Hardware Tessellated Objects
  • Real-time 3D Reconstruction at Scale using Voxel Hashing
  • Real-time Collision Detection for Dynamic Hardware Tessellated Objects
  • Real-time Expression Transfer for Facial Reenactment
  • Real-time Local Displacement using Dynamic GPU Memory Management
  • Real-Time Pixel Luminance Optimization for Dynamic Multi-Projection Mapping
  • Reality Forge: Interactive Dynamic Multi-Projection Mapping
  • Robust Blending and Occlusion Compensation in Dynamic Multi-Projection Mapping
  • Shape Adaptive Cut Lines
  • Spherical Fibonacci Mapping
  • State of the Art Report on Real-time Rendering with Hardware Tessellation
  • Stray-Light Compensation in Dynamic Projection Mapping
  • Visualization and Deformation Techniques for Entertainment and Training in Cultural Heritage
  • VolumeDeform: Real-time Volumetric Non-rigid Reconstruction

Multi-Resolution Attributes for Hardware Tessellated Objects

Dr.-Ing Henry Schäfer

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Hardware tessellation is one of the latest GPU features. Triangle or quad meshes are tessellated on-the-fly, where the tessellation level is chosen adaptively in a separate shader. The hardware tessellator only generates topology; attributes such as positions or texture coordinates of the newly generated vertices are determined in a domain shader. Typical applications of hardware tessellation are view dependent tessellation of parametric surfaces and displacement mapping. Often, the attributes for the newly generated vertices are stored in textures, which requires uv unwrapping, chartification, and atlas generation of the input mesh—a process that is time consuming and often requires manual intervention. In this paper, we present an alternative representation that directly stores optimized attribute values for typical hardware tessellation patterns and simply assigns these attributes to the generated vertices at render time. Using a multilevel fitting approach, the attribute values are optimized for several resolutions. Thereby, we require no parameterization, save memory by adapting the density of the samples to the content, and avoid discontinuities by construction. Our representation is optimally suited for displacement mapping: it automatically generates seamless, view-dependent displacement mapped models. The multilevel fitting approach generates better low-resolution displacement maps than simple downfiltering. By properly blending levels, we avoid artifacts such as popping or swimming surfaces. We also show other possible applications such as signal-optimized texturing or light baking. Our representation can be evaluated in a pixel shader, resulting in signal adaptive, parameterization-free texturing, comparable to PTex or Mesh Colors. Performance evaluation shows that our representation is on par with standard texture mapping and can be updated in real time, allowing for application such as interactive sculpting.

Chair of Visual Computing
(Lehrstuhl für Graphische Datenverarbeitung)

Cauerstraße 11
91058 Erlangen
Deutschland
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