PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing

TL;DR

PoliteCamera is a cooperative system that uses facial attribute analysis and neural networks to automatically blur strangers' faces in mobile photos upon request, protecting their privacy.

Contribution

It introduces a novel cooperative scheme with an ABCNN model to accurately identify and blur strangers' faces in photos, enhancing privacy protection.

Findings

ABCNN accurately predicts facial attributes.

PoliteCamera effectively blurs faces of requesting strangers.

System maintains high privacy protection in real-world tests.

Abstract

Camera is a standard on-board sensor of modern mobile phones. It makes photo taking popular due to its convenience and high resolution. However, when users take a photo of a scenery, a building or a target person, a stranger may also be unintentionally captured in the photo. Such photos expose the location and activity of strangers, and hence may breach their privacy. In this paper, we propose a cooperative mobile photographing scheme called PoliteCamera to protect strangers' privacy. Through the cooperation between a photographer and a stranger, the stranger's face in a photo can be automatically blurred upon his request when the photo is taken. Since multiple strangers nearby the photographer might send out blurring requests but not all of them are in the photo, an adapted balanced convolutional neural network (ABCNN) is proposed to determine whether the requesting stranger is in the photo based on facial attributes. Evaluations demonstrate that the ABCNN can accurately predict facial attributes and PoliteCamera can provide accurate privacy protection for strangers.