VizWiz-Priv: A Dataset for Recognizing the Presence and Purpose of Private Visual Information in Images Taken by Blind People

Danna Gurari, Qing Li, Chi Lin, Yinan Zhao, Anhong Guo, Abigale Stangl, Jeffrey P. Bigham; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 939-948

Abstract


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. It includes 8,862 regions showing private content across 5,537 images taken by blind people. Of these, 1,403 are paired with questions and 62% of those directly ask about the private content. Experiments demonstrate the utility of this data for predicting whether an image shows private information and whether a question asks about the private content in an image. The dataset is publicly-shared at http://vizwiz.org/data/.

Related Material


[pdf] [supp]
[bibtex]
@InProceedings{Gurari_2019_CVPR,
author = {Gurari, Danna and Li, Qing and Lin, Chi and Zhao, Yinan and Guo, Anhong and Stangl, Abigale and Bigham, Jeffrey P.},
title = {VizWiz-Priv: A Dataset for Recognizing the Presence and Purpose of Private Visual Information in Images Taken by Blind People},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}