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.
翻译:在本文中,我们引入了一种新的相机定位战略,用于在具有挑战性的工业环境(如工业部件检查)中拍摄图像序列。为了应对伤害标准 3D 重建管道的特殊外观,我们利用预知现场的方法,选择与某个地点大致相连的序列(称为锚)键框架。然后,我们的方法是按时间顺序查找每个框架的位置,同时反复更新一个强化的3D模型,该模型可以提供当前的相机位置和周围的3D结构。在一次关于实际工业形势的实验中,我们的方法可以在输入序列中将99%以上的框架本地化,而标准本地化方法无法重建完整的相机轨迹。