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Machine learning systems and methods for augmenting images

机译:机器学习系统和增强图像的方法

摘要

Disclosed is a method including receiving visual input comprising a human within a scene, detecting a pose associated with the human using a trained machine learning model that detects human poses to yield a first output, estimating a shape (and optionally a motion) associated with the human using a trained machine learning model associated that detects shape (and optionally motion) to yield a second output, recognizing the scene associated with the visual input using a trained convolutional neural network which determines information about the human and other objects in the scene to yield a third output, and augmenting reality within the scene by leveraging one or more of the first output, the second output, and the third output to place 2D and/or 3D graphics in the scene.
机译:公开了一种方法,该方法包括:接收场景中包括人的视觉输入;使用训练有素的机器学习模型来检测与该人相关联的姿势,该训练后的机器学习模型检测人的姿势以产生第一输出;估计与该人相关联的形状(以及可选地,运动)。人类使用训练有素的机器学习模型关联,该模型检测形状(以及可选地运动)以产生第二个输出,并使用训练后的卷积神经网络识别与视觉输入关联的场景,该网络确定关于人类和场景中要产生的其他对象的信息第三输出,并利用第一输出,第二输出和第三输出中的一个或多个将场景中的2D和/或3D图形放置在场景中,从而增强场景内的真实感。

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