用纯位姿约束优化多相机系统，提速同时保精度。
A Pose-only Geometric Constraint for Multi-Camera Pose Adjustment
- 构建统一相机模型，仅用位姿和基础观测隐式表示三维点
- 消除优化中的3D点参数，计算效率显著提升
- 适合需要高效位姿优化的多相机系统应用
多相机系统在视觉导航与三维场景重建中具备丰富的观测能力，但特征冗余常导致计算效率下降。这一问题在束调整中尤为突出，因其需对系统位姿和场景点进行非线性优化，计算开销大。本文提出一种针对多相机系统的纯位姿几何约束及相应位姿调整算法。首先利用广义相机模型建立多相机系统的统一表示；在此基础上，构建多相机纯位姿约束，通过两个基础观测及其关联位姿隐式表示一个三维场景点，从而实现投影几何的纯位姿表达。进而提出一种多相机位姿调整算法，将3D点从参数空间中移除，实现高效且聚焦的位姿优化。在合成数据集与真实世界数据集上的实验表明，该方法在计算效率上优于基线束调整方法，同时保持甚至提升了位姿估计精度。
原文摘要 · Abstract (English)
Multi-camera systems offer rich observation capabilities for visual navigation and 3D scene reconstruction; however, the resulting feature redundancy often compromises computational efficiency. This challenge is particularly pronounced during bundle adjustment, where the non-linear optimization of both system poses and scene points incurs substantial computational overhead. To address this challenge, this paper introduces a pose-only geometric constraint for multi-camera systems and proposes a corresponding pose adjustment algorithm. Specifically, we use generalized camera model to establish a unified representation of the multi-camera system. Building upon this model, we formulate the multi-camera pose-only constraint, which implicitly represents a 3D scene point using two base observations and their associated poses, thereby achieving a pose-only representation of the projection geometry. Subsequently, we introduce a multi-camera pose adjustment algorithm that eliminates 3D points from the parameter space, thereby achieving efficient and focused pose optimization. Experimental results on both synthetic and real-world datasets demonstrate that the proposed algorithm outperforms baseline bundle adjustment methods in computational efficiency, while maintaining or even improving pose estimation accuracy.
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