Facial cosmetics database and impact analysis on automatic face recognition

Eckert, Marie-Lena; Köse, Neslihan; Dugelay, Jean‐Luc

doi:10.1109/mmsp.2013.6659328

Cited by 31 publications

(38 citation statements)

References 10 publications

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“…Recent work has demonstrated the impact of commonly used facial makeup on automated face recognition systems [6,8,9,12,5], and automated face-based gender and age estimation systems [4]. Makeup can be used to alter the perceived (a) facial shape; (b) nose, mouth, eye and eye brow shape; (c) nose, mouth, eye and eye brow size; (d) facial contrast and (e) facial skin quality and color.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Considering the widespread use of makeup and its implications in altering facial appearance (e.g., facial aesthetics [7]), in this work we focus on the use of makeup for spoofing. Unlike previous work [6,8,9], where commonly used makeup was observed to affect face recognition systems by obscuring a person's identity, here we consider the scenario where makeup is used by an individual to mimic the facial appearance of another individual (see Figure 2). Current face spoof detection schemes either rely on physiological cues such as eye blinking, mouth movements, and macro-and micro-expression changes [19,16], or textural attributes of the face image [16,24,23,14].…”

Section: Background and Related Workmentioning

confidence: 99%

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Spoofing faces using makeup: An investigative study

Chen

Dantcheva

Swearingen

et al. 2017

2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)

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Makeup can be used to alter the facial appearance of a person. Previous studies have established the potential of using makeup to obfuscate the identity of an individual with respect to an automated face matcher. In this work, we analyze the potential of using makeup for spoofing an identity, where an individual attempts to impersonate another person's facial appearance. In this regard, we first assemble a set of face images downloaded from the internet where individuals use facial cosmetics to impersonate celebrities. We next determine the impact of this alteration on two different face matchers. Experiments suggest that automated face matchers are vulnerable to makeup-induced spoofing and that the success of spoofing is impacted by the appearance of the impersonator's face and the target face being spoofed. Further, an identification experiment is conducted to show that the spoofed faces are successfully matched at better ranks after the application of makeup. To the best of our knowledge, this is the first work that systematically studies the impact of makeup-induced face spoofing on automated face recognition.

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Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

Spoofing faces using makeup: An investigative study

Chen

Dantcheva

Swearingen

et al. 2017

2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)

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“…Recent studies have demonstrated the negative impact of facial cosmetics on the matching accuracy of automated face recognition systems [Dantcheva et al, 2012, Eckert et al, 2013. Such an impact has been attributed to the ability of makeup to alter the perceived shape, color and size of facial features, and skin appearance in a simple and cost efficient manner [Dantcheva et al, 2012].…”

Section: Introductionmentioning

confidence: 99%

Impact of Facial Cosmetics on Automatic Gender and Age Estimation Algorithms

Chen

Dantcheva

Ross

2014

Proceedings of the 9th International Conference on Computer Vision Theory and Applications

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Abstract:Recent research has established the negative impact of facial cosmetics on the matching accuracy of automated face recognition systems.In this paper, we analyze the impact of cosmetics on automated gender and age estimation algorithms. In this regard, we consider the use of facial cosmetics for (a) gender spoofing where male subjects attempt to look like females and vice versa, and (b) age alteration where female subjects attempt to look younger or older than they actually are. While such transformations are known to impact human perception, their impact on computer vision algorithms has not been studied. Our findings suggest that facial cosmetics can potentially be used to confound automated gender and age estimation schemes.

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“…Makeup as a potential form of disguise is analyzed separately by Eckert et al [4]. In the study, a variety of makeup such as shadow, blush, eyeliner, and lipstick has been applied to the skin, mouth and eyes.…”

Section: Disguisesmentioning

confidence: 99%

Digital Eye Modification A Countermeasure to Automated Face Recognition

Poster¹

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Digital Eye Modification A Countermeasure to Automated Face Recognition Domenick Poster III This thesis describes and assesses a series of subtle digital eye modification techniques and their impact on automated face detection and recognition. The techniques involve altering the relative positioning of a person's eyes in a photograph using a variety of horizontal and vertical movements local to the eye regions. Testing with Eigenfaces, Fisherfaces, and Circular Local Binary Pattern face recognition algorithms on a database of 40 subjects and over 4000 modified images shows these subtle geometric changes to the eyes can degrade automated face recognition accuracy by 40% or more. Certain modifications even lower the chance a face is detected at all by about 20%. The combined effect of particular eye modifications resulted in subjects being both detected and recognized less than 20% of time. These results indicate that nearly imperceptible modifications made to one or more key facial features may foil face recognition algorithms. iii vii A.2 Vertical Modification Rank-1 Accuracy of Non-Normalized Images (1 Training Image per Subject

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Facial cosmetics database and impact analysis on automatic face recognition

Cited by 31 publications

References 10 publications

Spoofing faces using makeup: An investigative study

Spoofing faces using makeup: An investigative study

Impact of Facial Cosmetics on Automatic Gender and Age Estimation Algorithms

Digital Eye Modification A Countermeasure to Automated Face Recognition

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