Our first tests with person correlation where performed with QR-Codes. In this example, we used QR codes to encode privacy policies. The overall goal of this experimental setup was to test person correlation inherently to the artifacts in which the privacy policies are encoded. We are not intending to use QR codes in a later stage of the project as they are big, intrusive and everything else but aesthetic. However, due to their feasibility for this particular test on person correlation they serve as an excellent baseline for investigation.
One of the essentials of the P3F framework is efficient and reliable face detection in order to correlate the persons on the picture with the artifacts used to encode the privacy policies.
Our results have shown, that false positives from the face detector can lead to very unpleasant effects for the users. In case of a fale positive, the P3F tags are assigned away from real persons to falsely detected faces that coincidentely happen to be nearer. Thus, they weaken the personal protection of the actual persons in the picture. We will address this problem by revising our framework and by testing several face detection algorithms that have been investigated in scientific publications and used in industrial applications.