通过三角一致性提升相机位姿估计的全局方向准确性
TriDE: Triangle-Consistent Translation Directions for Global Camera Pose Estimation
- 利用相机三角形一致性作为高阶验证信号，统一优化方向
- 在真实图像图上方向准确率显著提升，下游位姿估计更优
- 适合需要高精度全局位姿估计的三维重建场景
成对平移方向是全局结构光恢复中相机定位的关键输入。现有方法通常独立处理每对图像，得到的方向虽局部合理，但与其他相对方向不一致。为此，我们提出TriDE，利用相机三角形一致性作为高效的高阶验证信号。不同于求解敏感于初始化的复杂全局非线性优化问题，TriDE通过方向与其关联加权三角形间的消息传递，精炼不可靠的成对方向。该信息传播策略使我们在现实随机扰动模型下建立了精确恢复的强相变边界。在真实图像图上的实验表明，TriDE大幅提升了方向准确率，并获得更优的下游相机位姿，为局部成对估计与全局相机位姿几何之间提供了实用连接。
原文摘要 · Abstract (English)
Pairwise translation directions are a key input to camera location estimation in global structure-from-motion. Existing estimators usually process each image pair independently, producing directions that may be locally plausible but inconsistent with the other relative directions in the viewing graph. To jointly estimate the direction, we propose TriDE, which exploits camera-triangle consistency as an efficient higher-order verification signal. Instead of solving a costly global nonlinear optimization problem that is sensitive to initialization, TriDE refines unreliable pairwise directions through message passing between directions and their incident weighted triangles. This information propagation strategy enables us to establish a strong phase-transition bound for exact recovery under a realistic random corruption model. Experiments on real image graphs show that TriDE improves direction accuracy by a large margin and yields better downstream camera locations, providing a practical link between local pairwise estimation and global camera pose geometry.
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