用火星车图像重建可打印的3D地形模型，挑战低纹理与不完整观测。
Benchmarking stereo reconstruction for 3D printable Martian terrain models
- 基于NASA好奇号图像，用RAFT-Stereo估计立体深度并补全几何结构
- 在真实火星影像上，RAFT虽有更密深度图但边缘对齐差、重投影误差高
- 不同补全方法各有优劣：α形状保真但碎片多，泊松重建连贯但加伪结构
从火星漫游车图像重建可打印的3D地形模型极具挑战，因火星地形纹理稀少、形态不规则且部分可见。本文评估了一条从NASA好奇号图像中估计立体深度、补全几何结构并导出封闭OBJ网格的流程。在Middlebury数据集上，RAFT-Stereo优于半全局块匹配（SGBM），将视差平均绝对误差从3.22像素降至0.73像素，有效预测覆盖率从76.3%提升至100.0%。但在好奇号真实图像上，RAFT生成的更密集视差表现出较差的边缘对齐和更高的光度重投影误差，表明基准测试精度无法直接迁移到火星地形重建。几何补全显示局部保真与全局连通性间的权衡：α形状保留精确但碎片化结构，泊松重建生成更连贯网格但引入无支撑表面，确定性扩散填充基线居中但对立体质量敏感。总体而言，标准立体与补全方法可生成火星地形的可打印近似模型，但可靠重建需更强的领域特定验证。
原文摘要 · Abstract (English)
Reconstructing printable 3D models from Mars rover imagery is challenging because Martian terrain is low-texture, irregular, and partially observed. We evaluate a pipeline that estimates stereo depth from NASA Curiosity images, completes geometry, and exports watertight OBJ meshes. On Middlebury, RAFT-Stereo outperforms semi-global block matching (SGBM), reducing disparity MAE from 3.22px to 0.73px and increasing valid prediction coverage from 76.3% to 100.0%. On Curiosity imagery, however, RAFT's denser disparities show weaker edge alignment and higher photometric reprojection error, suggesting that benchmark accuracy does not directly transfer to Martian terrain reconstruction. Geometry completion demonstrates a tradeoff between local fidelity and global connectivity. We find that alpha shapes preserve accurate but fragmented structure, Poisson reconstruction produces more coherent meshes but adds unsupported surfaces, and a deterministic diffusion-fill baseline is intermediate but sensitive to stereo quality. Overall, standard stereo and completion methods can produce printable approximations of Martian terrain, but reliable reconstruction requires stronger domain-specific validation.
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