Stable and Scalable Bundle Adjustment of Holistic 3D Structures
Bundle Adjustment (BA) is a cornerstone of 3D computer vision and has benefited from decades of advances in sparse optimization and numerical methods. It was originally developed for jointly optimizing camera intrinsics, poses and sparse 3D points. While extensions incorporate lines and other primitives, integrating richer geometric structures such as parallelism, coplanarity, or wireframes often introduces significantly increased computational cost and reduced numerical stability. In this paper, we propose a unified framework that extends bundle adjustment to jointly optimize geometric features and higher-order relations. We first introduce a taxonomy that distinguishes scalable geometri...
| Authors | Shaohui Liu, Rémi Pautrat, Daniel Barath et al. |
|---|---|
| Primary category | cs.CV |
| Published | 3 September 2026 |
| Last updated at source | 3 September 2026 |
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