Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application 2017
DOI: 10.5220/0006131100390050
|View full text |Cite
|
Sign up to set email alerts
|

Automatic Generation and Detection of Visually Faultless Facial Morphs

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

1
124
0

Year Published

2017
2017
2023
2023

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 104 publications
(127 citation statements)
references
References 22 publications
1
124
0
Order By: Relevance
“…Several researchers become aware of the danger of morphing attacks and developed different forensic methods to detect this kind of fraud. In contrast to the already proposed methods, which are based on image degeneration [4], Binarized Statistical Image Features (BSIF) [5], neural networks [6], [7] or JPEG compression artifacts [8], we propose a method that is based on a physical illumination model. Illumination estimation to detect frauds was already studied in detail by [9], [10] to detect compositions of multiple photographs.…”
Section: Introductionmentioning
confidence: 99%
“…Several researchers become aware of the danger of morphing attacks and developed different forensic methods to detect this kind of fraud. In contrast to the already proposed methods, which are based on image degeneration [4], Binarized Statistical Image Features (BSIF) [5], neural networks [6], [7] or JPEG compression artifacts [8], we propose a method that is based on a physical illumination model. Illumination estimation to detect frauds was already studied in detail by [9], [10] to detect compositions of multiple photographs.…”
Section: Introductionmentioning
confidence: 99%
“…The morphing described in [1,4] are time consuming because it requires a manual retouch for more realistic appearance. To overcome this issue, Makrushin et al in [5] proposed an automatic splicing-based morphing algorithm to generate thousands of visually faultless facial morphs. In general, the quality of morphed images is 2-fold; (i) morphed images need to be visually faultless to human eyes (i.e.…”
Section: Introductionmentioning
confidence: 99%
“…These properties make splicing technique to pass the first morph quality measure, provided that both source images have similar skin color, but miserable regarding the second quality measure because splicing adopts geometry from one source image only and it may not look very similar to the other image. A combined morph technique was also proposed by [5] to overcome the limitations in the two previous algorithms. It warps the images into an average position first, then it cuts the facial regions, blending and finally stitching them back on to the warped image.…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations