Video-Based Camera Localization Using Anchor View Detection and Recursive 3D Reconstruction

TL;DR

This paper presents a novel camera localization method for industrial image sequences that uses anchor view detection and recursive 3D reconstruction to improve localization accuracy in challenging scenarios.

Contribution

The proposed approach introduces anchor view detection and recursive 3D model updating to enhance camera localization in difficult industrial environments.

Findings

Achieves over 99% frame localization accuracy in experiments.

Outperforms standard methods that fail to reconstruct complete trajectories.

Effective in challenging industrial inspection scenarios.

Abstract

In this paper we introduce a new camera localization strategy designed for image sequences captured in challenging industrial situations such as industrial parts inspection. To deal with peculiar appearances that hurt standard 3D reconstruction pipeline, we exploit pre-knowledge of the scene by selecting key frames in the sequence (called as anchors) which are roughly connected to a certain location. Our method then seek the location of each frame in time-order, while recursively updating an augmented 3D model which can provide current camera location and surrounding 3D structure. In an experiment on a practical industrial situation, our method can localize over 99% frames in the input sequence, whereas standard localization methods fail to reconstruct a complete camera trajectory.