基于 3D 区域指定目标的实时弱现实应用

Kaito Kobayashi, Masanobu Takahashi
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摘要

减弱现实(DR)是一种将背景图像覆盖在真实物体上,使其看起来好像该物体已从真实空间中移除的技术。本文介绍了一种采用深度学习的实时 DR 应用程序。DR 应用程序可以移除用户在使用智能手机拍摄的图像中定义的三维区域内的物体。通过指定包含要移除的目标对象的三维区域,可以对各种形状和大小的目标实现 DR,即使视角发生变化,也能移除指定的目标。为了实现快速准确的 DR,我们根据实验结果采用了合适的网络。此外,还改进了训练过程中的损失函数,以提高完成精度。然后,使用智能手机和笔记本电脑验证了 DR 应用程序在 10 fps 下的运行情况。
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Real-Time Diminished Reality Application Specifying Target Based on 3D Region
Diminished reality (DR) is a technology in which a background image is overwritten on a real object to make it appear as if the object has been removed from real space. This paper presents a real-time DR application that employs deep learning. A DR application can remove objects inside a 3D region defined by a user in images captured using a smartphone. By specifying the 3D region containing the target object to be removed, DR can be realized for targets with various shapes and sizes, and the specified target can be removed even if the viewpoint changes. To achieve fast and accurate DR, a suitable network was employed based on the experimental results. Additionally, the loss function during the training process was improved to enhance completion accuracy. Then, the operation of the DR application at 10 fps was verified using a smartphone and a laptop computer.
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