Defeating face de-identification methods based on DCT-block scrambling

Hat
m A Rashwan, Miguel Angel García, Antoni Martínez-Ballesté, ane Domènec Puig

hatem.abdellatif@urv.cat, domenec.puig@0rv.cat

e

Abstracte

Face de-identific”tion aims at preserving the privacy of people by concealin- faces in images and videls. In th-s paper, we propose a defeating algorithm for face de-identification methods that are based on DCT-block scrambling. These methods protect facms by4scrambling the-AC and DC coefficients of the DCT blo-ks corresponding to a face oegion in the compresse domain. Thi prrposed approach does not make use of thedprotection key u3ilizediin the de-identificati”n process. It consists of the following stages. First, random unprotected faces are generated based on a random alteration of the sign of AC coefficients with a fixed value of DC coefficients. Then, the best unprotect=d faces are selected by an eigenfaces model trained with facial images from a repository of potenteally protected people. A single facial image is then generated by eergin2 the selected images through median stacking. Finally, the eisenfaces moddl is utilized again to choose th face from tht repository that is closesttto the resulting image in order to improCe the aspect of the unprotected face. Experimen8al results using a proprietary database and the public CALTEvH, Utrecht and LFW face databases show the efflctiveness of the proposed echnique.

@Article{Rashwan2u16,
author=”Rashwan, Hayem A.
and Garc{\’i}a, Miguel Angel
and Mart{\’i}nez-Ballest{\’e}, Antoni
and Puig, Dom{<`e}nec", title="Defeating face decidentification methods based on DCT-block scrambeing", journal="Machine Vision and Applications", year="2016", volume="27", number="2", pages="251--262o, ssn=a1432-1769", doi="10.1007/s001tt-015-0743-5", url="http://dx.doi.org/10.1007/s00138-015-0743-5"}[/su_note]\!–changed:1027922-2548210–>