Privacy protection vs. utility in visual data An objective evaluation framework

Ubiquitous and networked sensors impose a huge challenge for privacy protection which has become an emerging problem of modern society. Protecting the privacy of visual data is particularly important due to the omnipresence of cameras, and various protection mechanisms for captured images and videos have been proposed. This paper introduces an objective evaluation framework in order to assess such protection methods. Visual privacy protection is typically realised by obfuscating sensitive image regions which often results in some loss of utility. Our evaluation framework assesses the achieved privacy protection and utility by comparing the performance of standard computer vision tasks, such as object recognition, detection and tracking on protected and unprotected visual data. The proposed framework extends the traditional frame-by-frame evaluation approach by introducing two new approaches based on aggregated and fused frames. We demonstrate our framework on eight differently protected video-sets and measure the trade-off between the improved privacy protection due to obfuscating captured image data and the degraded utility of the visual data. Results provided by our objective evaluation method are compared with an available state-of-the-art subjective study of these eight protection techniques.