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Inpainting in Omnidirectional Images for Privacy Protection

机译：全向图像修复以保护隐私

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摘要

Privacy protection is drawing more attention with the advances in image processing, visual and social media. Photo sharing is a popular activity, which also brings the concern of regulating permissions associated with shared content. This paper presents a method for protecting user privacy in omnidirectional media, by removing parts of the content selected by the user, in a reversible manner. Object removal is carried out using three different state-of-the-art inpainting methods, employed over the mask drawn in the viewport domain so that the geometric distortions are minimized. The perceived quality of the scene is assessed via subjective tests, comparing the proposed method against inpainting employed directly on the equirectangular image. Results on distinct contents indicate our object removal methodology on the viewport enhances perceived quality, thereby improves privacy protection as the user is able to hide objects with less distortion in the overall image.
机译：随着图像处理，视觉和社交媒体的发展，隐私保护越来越引起人们的关注。照片共享是一种流行的活动，这也带来了对与共享内容关联的权限进行监管的担忧。本文提出了一种通过以可逆方式删除用户选择的部分内容来保护全向媒体中用户隐私的方法。使用在视口域中绘制的蒙版上使用的三种不同的最新修复方法来执行对象移除，以使几何变形最小化。通过主观测试评估场景的感知质量，将建议的方法与直接在等矩形图像上使用的修补进行比较。不同内容上的结果表明，我们在视口上的对象移除方法提高了感知质量，从而提高了隐私保护，因为用户可以隐藏整体图像中失真较小的对象。

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