A Pose-only Geometric Constraint for Multi-Camera Pose Adjustment

TL;DR

This paper introduces a pose-only geometric constraint and an efficient pose adjustment algorithm for multi-camera systems, reducing computational overhead in pose optimization while maintaining accuracy.

Contribution

It proposes a novel pose-only constraint using a generalized camera model and a pose adjustment method that eliminates 3D points for faster optimization.

Findings

Outperforms baseline bundle adjustment in computational efficiency

Maintains or improves pose estimation accuracy

Validated on synthetic and real-world datasets

Abstract

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.