We consider the problem of tracking the 6D pose of a moving RGB-D camera in a neural scene representation. Different such representations have recently emerged, and we investigate the suitability of them for the task of camera tracking. In particular, we propose to track an RGB-D camera using a signed distance field-based representation and show that compared to density-based representations, tracking can be sped up, which enables more robust and accurate pose estimates when computation time is limited.
翻译:我们考虑了在神经场景演示中跟踪移动的RGB-D相机6D外形的问题。 最近出现了不同的这种外形,我们调查了它们是否适合用于相机跟踪任务。 特别是,我们提议使用签名的远程现场演示来跟踪RGB-D外观摄像头,并表明与基于密度的演示相比,跟踪可以加快,这样在计算时间有限时,可以更稳健、更准确地做出估计。