|
Title
|
|
|
|
Face detection hindering
| |
|
Author
|
|
|
|
| |
|
Abstract
|
|
|
|
| In this paper, we develop a face detection hindering method, as a means of preventing the threats to people's privacy, automatic video analysis may pose. Face detection in images or videos is the first step in human-centered video analysis to be followed, e.g. by automatic face recognition. Therefore, by hindering face detection, we also render automatic face recognition improbable. To this end, we examine the application of two methods. First, we consider a naive approach, i.e., we simply use additive or impulsive noise to the input image, until the point where the face cannot be automatically detected anymore. Second, we examine the application of the SVD-DID face de-identification method. Our experimental results denote that both methods attain high face detection failure rates. |
| |
|
Language
|
|
|
|
English
| |
|
Source (book)
|
|
|
|
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 14-16 November, 2017, Montreal, QC, Canada
| |
|
Publication
|
|
|
|
New york
:
2017
| |
|
ISBN
|
|
|
|
978-1-5090-5990-4
| |
|
DOI
|
|
|
|
10.1109/GLOBALSIP.2017.8308673
| |
|
Volume/pages
|
|
|
|
(2017)
, p. 403-407
| |
|
ISI
|
|
|
|
000450053100081
| |
|
Full text (Publisher's DOI)
|
|
|
|
| |
|