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SYSTEMS AND METHODS FOR TRAINING IMAGE DETECTION SYSTEMS FOR AUGMENTED AND MIXED REALITY APPLICATIONS

机译:用于训练增强和混合现实应用的图像检测系统的系统和方法

摘要

Described are system, method, and computer-program product embodiments for developing an object detection model. The object detection model may detect a physical object in an image of a real world environment. A system can automatically generate a plurality of synthetic images. The synthetic images can be generated by randomly selecting parameters of the environmental features, camera intrinsics, and a target object. The system may automatically annotate the synthetic images to identify the target object. In some embodiments, the annotations can include information about the target object determined at the time the synthetic images are generated. The object detection model can be trained to detect the physical object using the annotated synthetic images. The trained object detection model can be validated and tested using at least one image of a real world environment. The image(s) of the real world environment may or may not include the physical object.
机译:描述是用于开发对象检测模型的系统,方法和计算机程序产品实施例。对象检测模型可以检测真实世界环境的图像中的物理对象。系统可以自动生成多个合成图像。可以通过随机选择环境特征,摄像机内在机构和目标对象的参数来生成合成图像。系统可以自动注释合成图像以识别目标对象。在一些实施例中,注释可以包括关于在生成合成图像时确定的目标对象的信息。可以使用注释的合成图像训练对象检测模型以检测物理对象。培训的物体检测模型可以使用真实世界环境的至少一个图像进行验证和测试。现实世界环境的图像可能或可能不包括物理对象。

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