Video-Based Camera Localization Using Anchor View Detection and Recursive 3D Reconstruction
This addresses camera localization for industrial inspection, but it is incremental as it builds on existing 3D reconstruction methods with scene pre-knowledge.
The paper tackles camera localization in challenging industrial scenes by using anchor view detection and recursive 3D reconstruction, achieving over 99% frame localization in experiments where standard methods fail.
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.