A MIXTURE MODEL FOR ROBUST REGISTRATION IN KINECT SENSOR

机译：运动传感器中鲁棒配准的混合模型

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The Microsoft Kinect sensor has been widely used in many applications, but it suffers from the drawback of low registration precision between color image and depth image. In this paper, we present a robust method to improve the registration precision by a mixture model that can handle multiply images with the nonparametric model. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS).The estimation is performed by the EM algorithm which by also estimating the variance of the prior model is able to obtain good estimates. We illustrate the proposed method on the public available dataset. The experimental results show that our approach outperforms the baseline methods.

机译：Microsoft Kinect传感器已在许多应用程序中广泛使用，但是它受到彩色图像和深度图像之间配准精度低的缺点的困扰。在本文中，我们提出了一种鲁棒的方法，可以通过混合模型提高配准精度，该模型可以处理非参数模型的多重图像。我们在重现内核希尔伯特空间（RKHS）中对对应关系施加非参数几何约束作为先验分布。估算是由EM算法执行的，该算法还可以估算先验模型的方差，从而可以获得良好的估算值。我们在公共数据集上说明了所提出的方法。实验结果表明，我们的方法优于基线方法。

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《International symposium on multispectral image processing and pattern recognition》|2017年|1060906.1-1060906.5|共5页
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Li Peng; Huabing Zhou; Shengguo Zhu;
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EM; Image registration; Kinect sensor;

机译：EM;图像配准; Kinect传感器;

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2. A robust non-rigid point set registration method based on inhomogeneous Gaussian mixture models [J] . Deng Wanxia, Zou Huanxin, Guo Fang, The Visual Computer . 2018,第10期

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3. A robust aerial image registration method using Gaussian mixture models [J] . Chuan Wu, Yuanyuan Wang, Hamid Reza Karimi Neurocomputing . 2014,第nova20期

机译：使用高斯混合模型的稳健航空影像配准方法
4. A MIXTURE MODEL FOR ROBUST REGISTRATION IN KINECT SENSOR [C] . Li Peng, Huabing Zhou, Shengguo Zhu SPIE Conference on Multispectral Image Processing and Pattern Recognition . 2017

机译：Kinect传感器鲁棒配准的混合模型
5. Robust and Efficient Semantic Sensor Registration for Mobile Robotics in Unorganized, Natural, Scenes [D] . ?Parkison, Steven A. 2020

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6. Accurate and Robust Non-rigid Point Set Registration using Student’s-t Mixture Model with Prior Probability Modeling [O] . Zhiyong Zhou, Jianfei Tu, Chen Geng, -1

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7. Accurate and Robust Non-rigid Point Set Registration using Student’s-t Mixture Model with Prior Probability Modeling [O] . Zhiyong Zhou, Jianfei Tu, Chen Geng, 2018

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8. Response of the Sandia Robust wide range hydrogen sensor to H(sub 2)-O(sub 2) mixtures [R] . Hughes, R. C. , Moreno, D. J. , Jenkins, M. W. , 1994

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A MIXTURE MODEL FOR ROBUST REGISTRATION IN KINECT SENSOR

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