Inpainting in Omnidirectional Images for Privacy Protection

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.