首页> 外国专利> EMPLOYING THREE-DIMENSIONAL (3D) DATA PREDICTED FROM TWO-DIMENSIONAL (2D) IMAGES USING NEURAL NETWORKS FOR 3D MODELING APPLICATIONS AND OTHER APPLICATIONS

EMPLOYING THREE-DIMENSIONAL (3D) DATA PREDICTED FROM TWO-DIMENSIONAL (2D) IMAGES USING NEURAL NETWORKS FOR 3D MODELING APPLICATIONS AND OTHER APPLICATIONS

机译:使用神经网络从二维(2D)图像中预测的三维(3D)数据用于3D建模应用程序和其他应用程序

摘要

The disclosed subject matter is directed to employing machine learning models configured to predict 3D data from 2D images using deep learning techniques to derive 3D data for the 2D images. In some embodiments, a method is provided that comprises employing, by a system comprising a processor, one or more three-dimensional data from two-dimensional data (3D-from-2D) neural network models to derive three-dimensional data from one or more two-dimensional images captured of an object or environment from a current perspective of the object or environment viewed on or through a display of the device. The method further comprises, determining, by the system, a position for integrating a graphical data object on or within a representation of the object or environment viewed on or through the display based on the current perspective and the three-dimensional data.
机译:所公开的主题涉及采用机器学习模型,该机器学习模型被配置为使用深度学习技术从2D图像预测3D数据以导出2D图像的3D数据。在一些实施例中,提供了一种方法,该方法包括由包括处理器的系统采用来自二维数据(3D-from-2D)神经网络模型的一个或多个三维数据来从一个或多个神经网络中导出三维数据。从在设备的显示器上或通过设备的显示器查看的对象或环境的当前角度捕获的对象或环境的更多二维图像。该方法还包括由系统基于当前透视图和三维数据确定用于将图形数据对象集成在在显示器上或通过显示器观看的对象或环境的表示之上或之内的位置。

著录项

  • 公开/公告号US2019026958A1

    专利类型

  • 公开/公告日2019-01-24

    原文格式PDF

  • 申请/专利权人 MATTERPORT INC.;

    申请/专利号US201816141649

  • 发明设计人 DAVID ALAN GAUSEBECK;BABAK ROBERT SHAKIB;

    申请日2018-09-25

  • 分类号G06T19/20;H04N13/10;H04N13/156;H04N13/204;H04N13/106;H04N13/246;

  • 国家 US

  • 入库时间 2022-08-21 12:05:53

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