Plastic Surgery: An Obstacle for Deep Face Recognition?

Rathgeb, Christian; Didem, Dogan; Stockhardt, Fabian; Marsico, Maria De; Busch, Christoph

doi:10.1109/cvprw50498.2020.00411

Cited by 12 publications

(9 citation statements)

References 25 publications

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“…In [22] the authors collected a database of 900 individuals for analysing the effect of plastic surgery and found that the tested algorithms were unable to effectively account for the appearance changes caused by plastic surgery. More recently, Rathgeb et al showed in [23], using a database of mostly ICAO-quality face images [24] captured before and after various types of facial plastic surgeries, that different tested state-of-the-art face recognition systems maintained almost perfect verification performance at an operationally relevant threshold corresponding to a False Match Rate (FMR) of 0.1%. Numerous works have addressed the impact of temporary alterations on face recognition systems.…”

Section: B Facial Alterationsmentioning

confidence: 99%

Face Beneath the Ink: Synthetic Data and Tattoo Removal with Application to Face Recognition

Ibsen¹,

Rathgeb²,

Drozdowski³

et al. 2022

Preprint

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Systems that analyse faces have seen significant improvements in recent years and are today used in numerous application scenarios. However, these systems have been found to be negatively affected by facial alterations such as tattoos. To better understand and mitigate the effect of facial tattoos in facial analysis systems, large datasets of images of individuals with and without tattoos are needed. To this end, we propose a generator for automatically adding realistic tattoos to facial images. Moreover, we demonstrate the feasibility of the generation by training a deep learning-based model for removing tattoos from face images. The experimental results show that it is possible to remove facial tattoos from real images without degrading the quality of the image. Additionally, we show that it is possible to improve face recognition accuracy by using the proposed deep learning-based tattoo removal before extracting and comparing facial features.

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Section: B Facial Alterationsmentioning

confidence: 99%

Face Beneath the Ink: Synthetic Data and Tattoo Removal with Application to Face Recognition

Ibsen¹,

Rathgeb²,

Drozdowski³

et al. 2022

Preprint

Self Cite

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show abstract

“…More recently, Rathgeb et al. [21] introduced a new database of plastic surgery images which are mostly compliant with the ICAO quality requirements [22]. Using the new database as well as the database proposed in [20], Rathgeb et al.…”

Section: Related Workmentioning

confidence: 99%

“…They concluded that more work should be done towards designing algorithms capable of dealing with the appearance changes occurring as a result of a facial plastic surgery operation. More recently, Rathgeb et al [21] introduced a new database of plastic surgery images which are mostly compliant with the ICAO quality requirements [22]. Using the new database as well as the database proposed in [20], Rathgeb et al showed that the impact of plastic surgery on state-of-theart commercial and open-source face recognition systems is less significant than initially reported by other researchers.…”

Section: Physical Facial Manipulationsmentioning

confidence: 99%

Impact of facial tattoos and paintings on face recognition systems

et al. 2021

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In recent years, face recognition technologies have shown impressive recognition performance, mainly due to recent developments in deep convolutional neural networks. Notwithstanding those improvements, several challenges which affect the performance of face recognition systems remain. The authors investigate the impact that facial tattoos and paintings have on current face recognition systems. To this end, they first collected an appropriate database containing image-pairs of individuals with and without facial tattoos or paintings. The assembled database was used to evaluate how facial tattoos and paintings affect the detection, quality estimation, as well as the feature extraction and comparison modules of a face recognition system. The impact on these modules was evaluated using state-of-the-art open-source and commercial systems. The obtained results show that facial tattoos and paintings affect all the tested modules, especially for images where a large area of the face is covered with tattoos or paintings. The authors' work is an initial case study and indicates a need to design algorithms which are robust to the visual changes caused by facial tattoos and paintings.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…They concluded that more work should be done towards designing algorithms capable of dealing with the appearance changes occurring as a result of a facial plastic surgery operation. More recently, Rathgeb et al [21] introduced a new database of plastic surgery images which are mostly compliant with the ICAO quality requirements [22]. Using the new database as well as the database proposed in [20], Rathgeb et al showed that the impact of plasticsurgery on state-of-the-art commercial and open-source face recognition systems is less significant than initially reported by other researchers.…”

Section: A Physical Facial Manipulationsmentioning

confidence: 99%

Impact of Facial Tattoos and Paintings on Face Recognition Systems

Ibsen,

Rathgeb,

Fink

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

In the past years, face recognition technologies have shown impressive recognition performance, mainly due to recent developments in deep convolutional neural networks. Notwithstanding those improvements, several challenges which affect the performance of face recognition systems remain. In this work, we investigate the impact that facial tattoos and paintings have on current face recognition systems. To this end, we first collected an appropriate database containing image-pairs of individuals with and without facial tattoos or paintings. The assembled database was used to evaluate how facial tattoos and paintings affect the detection, quality estimation, as well as the feature extraction and comparison modules of a face recognition system. The impact on these modules was evaluated using stateof-the-art open-source and commercial systems. The obtained results show that facial tattoos and paintings affect all the tested modules, especially for images where a large area of the face is covered with tattoos or paintings. Our work is an initial casestudy and indicates a need to design algorithms which are robust to the visual changes caused by facial tattoos and paintings.

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Plastic Surgery: An Obstacle for Deep Face Recognition?

Cited by 12 publications

References 25 publications

Face Beneath the Ink: Synthetic Data and Tattoo Removal with Application to Face Recognition

Face Beneath the Ink: Synthetic Data and Tattoo Removal with Application to Face Recognition

Impact of facial tattoos and paintings on face recognition systems

Impact of Facial Tattoos and Paintings on Face Recognition Systems

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