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System and method for training a neural network for visual localization based upon learning objects-of-interest dense match regression

机译:基于学习对象的对象密集的匹配回归训练神经网络的系统和方法

摘要

A method for training, using a plurality of training images with corresponding six degrees of freedom camera pose for a given environment and a plurality of reference images, each reference image depicting an object-of-interest in the given environment and having a corresponding two-dimensional to three-dimensional correspondence for the given environment, a neural network to provide visual localization by: for each training image, detecting and segmenting object-of-interest in the training image; generating a set of two-dimensional to two-dimensional matches between the detected and segmented objects-of-interest and corresponding reference images; generating a set of two-dimensional to three-dimensional matches from the generated set of two-dimensional to two-dimensional matches and the two-dimensional to three-dimensional correspondences corresponding to the reference images; and determining localization, for each training image, by solving a perspective-n-point problem using the generated set of two-dimensional to three-dimensional matches.
机译:用于训练的方法,使用具有对应于给定环境的相应六个自由度摄像机的多个训练图像和多个参考图像,每个参考图像描绘给定环境中的对象并具有相应的两个 - 对给定环境的三维对应关系,一个神经网络提供视觉定位:对于每个训练图像,检测和分割训练图像的对象;在检测到的和分段对象和相应的参考图像之间生成一组二维与二维匹配;从生成的二维与二维匹配和与参考图像相对应的三维对应关系生成一组二维与三维匹配;通过使用所生成的二维与三维匹配来解决透视-N点问题来确定本地化。

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