Thermoxels：一种基于体素生成可仿真三维热模型的方法
Thermoxels: a voxel-based method to generate simulation-ready 3D thermal models
AI总结：
本文提出Thermoxels，一种基于体素的方法，从稀疏RGB和热图像生成包含几何与温度信息且兼容有限元分析的四面体网格，用于建筑热评估与热传导模拟。
摘要：
在欧盟，建筑占能源使用的42%和温室气体排放的35%。由于大多数现有建筑到2050年仍将使用，改造对于减排至关重要。然而，当前的建筑评估方法主要依赖定性热成像，这限制了基于数据驱动的节能决策。另一方面，使用有限元分析（FEA）的定量评估能提供精确的见解，但需要人工CAD设计，既繁琐又容易出错。三维重建的最新进展，如神经辐射场（NeRF）和高斯泼溅（Gaussian Splatting），能够从稀疏图像中实现精确的三维建模，但缺乏FEA所需的明确定义的体积及其之间的界面。我们提出Thermoxels，一种新颖的基于体素的方法，能够从一组稀疏的RGB和热图像生成FEA兼容的模型，包括几何形状和温度。Thermoxels以成对的RGB和热图像作为输入，将场景的几何形状表示为一组包含颜色和温度信息的体素。优化后，通过一个简单的过程将Thermoxels的模型转换为与FEA兼容的四面体网格。我们展示了Thermoxels生成三维场景RGB+热网格的能力，超越了其他最先进的方法。为了展示Thermoxels模型的实际应用，我们使用FEA进行了简单的热传导模拟，从Thermoxels热重建定义的初始状态实现了收敛。此外，我们将Thermoxels的图像合成能力与当前最先进的方法进行了比较，展示了具有竞争力的结果，并讨论了现有指标在评估网格质量方面的局限性。
英文摘要：
In the European Union, buildings account for 42% of energy use and 35% of greenhouse gas emissions. Since most existing buildings will still be in use by 2050, retrofitting is crucial for emissions reduction. However, current building assessment methods rely mainly on qualitative thermal imaging, which limits data-driven decisions for energy savings. On the other hand, quantitative assessments using finite element analysis (FEA) offer precise insights but require manual CAD design, which is tedious and error-prone. Recent advances in 3D reconstruction, such as Neural Radiance Fields (NeRF) and Gaussian Splatting, enable precise 3D modeling from sparse images but lack clearly defined volumes and the interfaces between them needed for FEA. We propose Thermoxels, a novel voxel-based method able to generate FEA-compatible models, including both geometry and temperature, from a sparse set of RGB and thermal images. Using pairs of RGB and thermal images as input, Thermoxels represents a scene's geometry as a set of voxels comprising color and temperature information. After optimization, a simple process is used to transform Thermoxels' models into tetrahedral meshes compatible with FEA. We demonstrate Thermoxels' capability to generate RGB+Thermal meshes of 3D scenes, surpassing other state-of-the-art methods. To showcase the practical applications of Thermoxels' models, we conduct a simple heat conduction simulation using FEA, achieving convergence from an initial state defined by Thermoxels' thermal reconstruction. Additionally, we compare Thermoxels' image synthesis abilities with current state-of-the-art methods, showing competitive results, and discuss the limitations of existing metrics in assessing mesh quality.
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