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Plane-Fitting Robust Registration for Complex 3D Models

机译:复杂3D模型的平面稳健注册

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In surgery planning, forensic and archeology, there is a need to perform analysis and synthesis of complex 3D models. One common first step of 3D model analysis and synthesis is to register a reference model to a target model using similarity transformation. In practice, the models usually contain noise and outliers, and are sometimes incomplete. These facts make the 3D similarity registration challenging. Existing similarity registration methods such as Iterative Closest Point algorithm (ICP) [1] and Fractional Iterative Closest Point algorithm (FICP) [2] are misled by the outliers and are not able to register these models properly. This paper presents a plane-fitting registration algorithm that is more robust than existing registration algorithms. It achieves its robustness by ensuring that the symmetric plane of the reference model is registered to the planar landmarks of the target model. Experiments on patients’ skull models show that the proposed algorithm is robust, accurate and efficient in registering complex models.
机译:在手术规划,法医和考古学中,需要进行复杂3D模型的分析和合成。 3D模型分析和合成的一个常见第一步是使用相似性转换将参考模型注册到目标模型。在实践中,模型通常包含噪声和异常值,有时是不完整的。这些事实使3D相似性注册具有挑战性。现有的相似性登记方法如迭代最接近点算法(ICP)[1]和分数迭代最接近点算法(FICP)[2]被异常值误导,并且无法正确注册这些模型。本文介绍了比现有的注册算法更强大的平面拟合配准算法。它通过确保参考模型的对称平面已经注册到目标模型的平面标记来实现其鲁棒性。患者颅骨模型的实验表明,该算法在注册复杂模型方面是坚固,准确和高效的。

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