ABSTRACT
Mesh repair is a long-standing challenge in computer graphics and related fields. Converting defective meshes into watertight manifold meshes can greatly benefit downstream applications such as geometric processing, simulation, fabrication, learning, and synthesis. In this work, by assuming the model is visually correct, we first introduce three visual measures for visibility, orientation, and openness, based on ray-tracing. We then present a novel mesh repair framework incorporating visual measures with several critical steps, i.e., open surface closing, face reorientation, and global optimization, to effectively repair meshes with defects (e.g., gaps, holes, self-intersections, degenerate elements, and inconsistent orientations) and preserve visual appearances. Our method reduces unnecessary mesh complexity without compromising geometric accuracy or visual quality while preserving input attributes such as UV coordinates for rendering. We evaluate our approach on hundreds of models randomly selected from ShapeNet and Thingi10K, demonstrating its effectiveness and robustness compared to existing approaches.
ABSTRACT
Image-space line integral convolution (LIC) is a popular scheme for visualizing surface vector fields due to its simplicity and high efficiency. To avoid inconsistencies or color blur during the user interactions, existing approaches employ surface parameterization or 3D volume texture schemes. However, they often require expensive computation or memory cost, and cannot achieve consistent results in terms of both the granularity and color distribution on different scales. This paper introduces a novel image-space surface flow visualization approach that preserves the coherence during user interactions. To make the noise texture under different viewpoints coherent, we propose to precompute a sequence of mipmap noise textures in a coarse-to-fine manner for consistent transition, and map the textures onto each triangle with randomly assigned and constant texture coordinates. Further, a standard image-space LIC is performed to generate the flow texture. The proposed approach is simple and GPU-friendly, and can be easily combined with various texture-based flow visualization techniques. By leveraging viewpoint-dependent backward tracing and mipmap noise phase, our method can be incorporated with the image-based flow visualization (IBFV) technique for coherent visualization of unsteady flows. We demonstrate consistent and highly efficient flow visualization on a variety of data sets.
