用双层边缘信息提升低纹理区域的三维重建精度
Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization
- 引入精细与粗略双重边缘信息增强平面建模鲁棒性
- 在ETH3D和Tanks & Temples上达到当前最佳性能
- 适合关注低纹理场景三维重建的研究者
低纹理区域的三维重建是多视图立体（MVS）中的重要研究方向。近年来，传统MVS方法通过构建平面模型在低纹理区域表现优异，但常面临物体边界交叉和感知范围受限等问题，影响平面建模的鲁棒性。基于此前工作APD-MVS，本文提出DPE-MVS方法，通过引入双层级精确边缘信息（包括细边缘与粗边缘），增强平面建模的鲁棒性，从而提升低纹理区域的重建精度。此外，利用边缘信息优化了传统PatchMatch MVS的采样策略，提出自适应块大小调整方法，以改进随机与低纹理区域的匹配代价计算。该方法在ETH3D和Tanks & Temples基准测试中均取得领先效果，尤其在ETH3D上超越所有已发表方法。
原文摘要 · Abstract (English)
The reconstruction of low-textured areas is a prominent research focus in multi-view stereo (MVS). In recent years, traditional MVS methods have performed exceptionally well in reconstructing low-textured areas by constructing plane models. However, these methods often encounter issues such as crossing object boundaries and limited perception ranges, which undermine the robustness of plane model construction. Building on previous work (APD-MVS), we propose the DPE-MVS method. By introducing dual-level precision edge information, including fine and coarse edges, we enhance the robustness of plane model construction, thereby improving reconstruction accuracy in low-textured areas. Furthermore, by leveraging edge information, we refine the sampling strategy in conventional PatchMatch MVS and propose an adaptive patch size adjustment approach to optimize matching cost calculation in both stochastic and low-textured areas. This additional use of edge information allows for more precise and robust matching. Our method achieves state-of-the-art performance on the ETH3D and Tanks & Temples benchmarks. Notably, our method outperforms all published methods on the ETH3D benchmark.
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