动态场景中多相机设置的鲁棒帧配准

Xu Zhao, Zhong Zhou, Y. Duan, Wei Wu
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引用次数: 0

摘要

在本文中,我们提出了一种新的方法来注册帧从多个相机到一致的全球尺度。假设在多个相机设置中观察到移动物体,我们使用初始帧来创建一个全局参考结构,其中使用基于ransac的配准算法估计每个新帧的姿态变化。我们进一步将配准方法与其他最先进的技术相结合,以比传统方法使用的相机数量更少的方式构建高质量的3D重建系统。实验结果表明,该方法比运动方法中单眼结构的配准效果更好,更经济。在各种具有挑战性的真实世界多摄像机视频数据集上的三维重建结果也证明了我们的方法的可行性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Frame Registration for Multiple Camera Setups in Dynamic Scenes
In this paper, we propose a novel method to register frames from multiple cameras into a consistent global scale. Assuming a moving object is observed in multiple camera setups, we use initial frames to create a global reference structure where the pose variation of each new frame is estimated using a RANSAC-based registration algorithm. We further combine the registration method with other state-of the-art techniques to build a high quality 3D reconstruction system with a smaller number of cameras than used by more traditional methods. Experimental results show that our method performs better and is more economical than the registration of separate monocular structures from motion methods. 3D reconstruction results on various challenging real world multi-camera video datasets also illustrate the feasibility and robustness of our method.
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