论文标题
现实世界中的纹理事物：用现代照片重建工具生成的纹理模型的存储库
Real-World Textured Things: a Repository of Textured Models Generated with Modern Photo-Reconstruction Tools
论文作者
论文摘要
我们目睹了使用自动照片重建工具从现实世界中捕获的纹理3D模型的扩散。该类别的数字3D模型具有独特的特征和缺陷，尤其是关于它们的参数化 - 使它们与源自其他更传统的来源的3D模型截然不同。我们通过收集大量代表并根据几个指标来定量评估其质量来研究这类3D模型。其中包括我们设计的新不变度度量，以评估紫外线图的碎片化，这是阻碍这些模型可用性的主要弱点之一。我们的结果回到了广泛共同的观念，即此类模型不适合在下游应用程序（例如视频游戏）中直接使用，并且需要具有挑战性的处理步骤。遗憾的是，现有的自动几何处理工具并不总是符合任务：例如，由于网格不一致，几何和拓扑噪声，过度分辨率或其他因素，我们验证了紫外线优化的可用工具通常会失败；此外，即使产生输出，它也很少对输入（根据上述措施）进行显着改善。因此，我们认为需要在此类模型上专门针对进一步的进步。为了实现这一目标，我们分享了我们以新的公共存储库，现实世界纹理的事物（RWTT）的形式收集的模型，这是对系统的现场测试和比较算法的基准。 RWTT由568个精心选择的纹理3D模型组成，代表了所有主要现代现成的照片重建工具。该存储库可在http://texturedmesh.isti.cnr.it/上获得，并且可以通过在实验过程中收集的元数据进行浏览，并配备了一种工具TexMetro，为通用UV映射的数据集提供了相同的度量。
We are witnessing a proliferation of textured 3D models captured from the real world with automatic photo-reconstruction tools. Digital 3D models of this class come with a unique set of characteristics and defects -- especially concerning their parametrization -- setting them starkly apart from 3D models originating from other, more traditional, sources. We study this class of 3D models by collecting a significant number of representatives and quantitatively evaluating their quality according to several metrics. These include a new invariant metric we design to assess the fragmentation of the UV map, one of the main weaknesses hindering the usability of these models. Our results back the widely shared notion that such models are not fit for direct use in downstream applications (such as videogames), and require challenging processing steps. Regrettably, existing automatic geometry processing tools are not always up to the task: for example, we verify that available tools for UV optimization often fail due mesh inconsistencies, geometric and topological noise, excessive resolution, or other factors; moreover, even when an output is produced, it is rarely a significant improvement over the input (according to the aforementioned measures). Therefore, we argue that further advancements are required specifically targeted at this class of models. Towards this goal, we share the models we collected in the form of a new public repository, Real-World Textured Things (RWTT), a benchmark to systematic field-test and compare algorithms. RWTT consists of 568 carefully selected textured 3D models representative of all the main modern off-the-shelf photo-reconstruction tools. The repository is available at http://texturedmesh.isti.cnr.it/ and is browsable by metadata collected during experiments, and comes with a tool, TexMetro, providing the same set of measures for generic UV mapped datasets.
