A Dataset for Recognizing the Presence and Purpose of Private Visual Information in Images Taken by Blind People
We introduce the first visual privacy dataset originating from people who are blind in order to better understand their privacy disclosures and to encourage the development of algorithms that can assist in preventing their unintended disclosures. For each image, we manually annotate private regions according to a taxonomy that represents privacy concerns relevant to their images. We also annotate whether the private visual information is needed to answer questions asked about the private images. These annotations serve as a critical foundation for designing algorithms that can decide (1) whether private information is in an image and (2) whether a question about an image asks about the private content in the image.