3,186 research outputs found
Review of the mathematical foundations of data fusion techniques in surface metrology
The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed
TwinTex: Geometry-aware Texture Generation for Abstracted 3D Architectural Models
Coarse architectural models are often generated at scales ranging from
individual buildings to scenes for downstream applications such as Digital Twin
City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as
twins from 3D dense reconstructions. However, these models typically lack
realistic texture relative to the real building or scene, making them
unsuitable for vivid display or direct reference. In this paper, we present
TwinTex, the first automatic texture mapping framework to generate a
photo-realistic texture for a piece-wise planar proxy. Our method addresses
most challenges occurring in such twin texture generation. Specifically, for
each primitive plane, we first select a small set of photos with greedy
heuristics considering photometric quality, perspective quality and facade
texture completeness. Then, different levels of line features (LoLs) are
extracted from the set of selected photos to generate guidance for later steps.
With LoLs, we employ optimization algorithms to align texture with geometry
from local to global. Finally, we fine-tune a diffusion model with a multi-mask
initialization component and a new dataset to inpaint the missing region.
Experimental results on many buildings, indoor scenes and man-made objects of
varying complexity demonstrate the generalization ability of our algorithm. Our
approach surpasses state-of-the-art texture mapping methods in terms of
high-fidelity quality and reaches a human-expert production level with much
less effort. Project page: https://vcc.tech/research/2023/TwinTex.Comment: Accepted to SIGGRAPH ASIA 202
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