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

Hajime Taira, Koki Onbe, Naoyuki Miyashita, M. Okutomi
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引用次数: 1

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 preknowledge 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.
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基于视频的摄像机定位:锚点视图检测和递归三维重建
在本文中,我们介绍了一种新的相机定位策略,该策略是为在工业零件检测等具有挑战性的工业环境中捕获的图像序列而设计的。为了处理伤害标准3D重建管道的特殊外观,我们通过选择序列中的关键帧(称为锚点)来利用场景的预知,这些关键帧大致连接到某个位置。然后,我们的方法按时间顺序寻找每帧的位置,同时递归更新一个增强的3D模型,该模型可以提供当前摄像机位置和周围的3D结构。在实际工业场景的实验中,我们的方法可以定位输入序列中99%以上的帧,而标准定位方法无法重建完整的相机轨迹。
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