首页> 外文会议>International conference on medical image computing and computer-assisted intervention;MICCAI 2010 >Accounting for Anisotropic Noise in Fine Registration of Time-of-Flight Range Data with High-Resolution Surface Data
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Accounting for Anisotropic Noise in Fine Registration of Time-of-Flight Range Data with High-Resolution Surface Data

机译:用高分辨率表面数据精细记录飞行时间范围数据中的各向异性噪声

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Time-of-Flight (ToF) sensors have become a considerable alternative to conventional surface acquisition techniques such as laser range scanning and stereo vision. Application of ToF cameras for the purpose of intra-operative registration requires matching of the noisy surfaces generated from ToF range data onto pre-interventionally acquired high-resolution surfaces. The contribution of this paper is twofold: Firstly, we present a novel method for fine rigid registration of noisy ToF data with high-resolution surface meshes taking into account both, the noise characteristics of ToF cameras and the resolution of the target mesh. Secondly, we introduce an evaluation framework for assessing the performance of ToF registration methods based on physically realistic ToF range data generated from a virtual scence. According to experiments within the presented evaluation framework, the proposed method outperforms the standard ICP algorithm with respect to correspondence search and transformation computation, leading to a decrease in the target registration error (TRE) of more than 70%.
机译:飞行时间(ToF)传感器已成为传统表面采集技术(例如激光测距和立体视觉)的重要替代品。为了术中配准的目的而应用ToF摄像机需要将从ToF范围数据生成的嘈杂表面匹配到预先干预地获取的高分辨率表面上。本文的贡献有两个方面:首先,我们考虑到ToF相机的噪声特性和目标网格的分辨率,提出了一种使用高分辨率表面网格对嘈杂的ToF数据进行精细的刚性配准的新方法。其次,我们引入了一个评估框架,用于基于从虚拟场景生成的物理逼真的ToF范围数据来评估ToF注册方法的性能。根据所提出的评估框架内的实验,在对应搜索和变换计算方面,所提出的方法优于标准ICP算法,从而使目标配准误差(TRE)降低了70%以上。

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