Effective evaluation of privacy protection techniques in visible and thermal imagery

 

 

 

 

 

This page provides a method for evaluating privacy protection techniques in visible and thermal imagery as proposed in [1]. Additionally, it also makes available below a new dataset, called TST-Priv, that contains synchronized visual and thermal sequences to facilitate the community in the evaluation of privacy protection techniques in particular and other tasks (e.g. object detection, tracking etc.) in general.

 

 

Overview

Privacy protection may be defined as replacing the original content in an image region with a new (less intrusive) content having modified target appearance information to make it less recognizable by applying a privacy protection technique. Indeed the development of privacy protection techniques needs also to be complemented with an established objective evaluation method to facilitate their assessment and comparison. Generally, existing evaluation methods rely on the use of subjective judgements or assume a specific target type in image data and use target detection and recognition accuracies to assess privacy protection. This work proposes a new annotation-free evaluation method that is neither subjective nor assumes a specific target type. It assesses two key aspects of privacy protection: protection and utility. Protection is quantified as an appearance similarity and utility is measured as a structural similarity between original and privacy-protected image regions. We performed an extensive experimentation using six challenging datasets (having 12 video sequences) including a new dataset (having six sequences) that contains visible and thermal imagery. The new dataset, called TST-Priv, is made available online below for community. We demonstrate effectiveness of the proposed method by evaluating six image-based privacy protection techniques, and also show comparisons of the proposed method over existing methods.

 

 

Dataset

Please download the TST-Priv dataset from here.

 

Please cite the following paper [1] (in your publications, presentations etc.), if you use the TST-Priv dataset.

 

 

Reference

[1] T. Nawaz, A. Berg, J. Ferryman, J. Ahlberg, M. Felsberg, Effective evaluation of privacy protection techniques in visible and thermal imagery, SPIE Journal of Electronic Imaging, Vol. 26, Issue 5, 051408, 2017. DOI: 10.1117/1.JEI.26.5.051408 [pdf]