De-identifying facial images using singular value decomposition and projections

被引：2

作者：

Chriskos, P. ^{[1
]}

Zoidi, O. ^{[1
]}

Tefas, A. ^{[1
]}

Pitas, I. ^{[1
,2
]}

机构：

[1] Aristotle Univ Thessloniki, Dept Informat, Thessaloniki 54124, Greece

[2] Univ Bristol, Dept Elect & Elect Engn, Bristol, Avon, England

来源：

MULTIMEDIA TOOLS AND APPLICATIONS | 2017年 / 76卷 / 03期

关键词：

Face de-idenification; Privacy protection; Singular value decomposition; Projections on hyperspheres;

D O I：

10.1007/s11042-016-4069-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, two methods are presented that manipulate images to hinder automatic face identification. They partly degrade image quality, so that humans can identify the persons in a scene, while face identification algorithms fail to do so. The approaches used involve: a) singular value decomposition (SVD) and b) image projections on hyperspheres. Simulation experiments verify that these methods reduce the percentage of correct face identification rate by over 90 %. Additionally, the final image is not degraded beyond recognition by humans, in contrast with the majority of other de-identification methods.

引用

页码：3435 / 3468

页数：34

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