Face Filters as Augmented Reality Art on Social Media

Herrington, Jessica

doi:10.1007/978-3-030-96863-2_16

Cited by 5 publications

(2 citation statements)

References 10 publications

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“…(Riccio, et al, 2022). When it comes to the general public's acceptance of AR filters as a viable artistic medium, the COVID-19 pandemic was a watershed event (Herrington, 2022), endowing filter designers with a crucial role in determining the technology's cultural and societal effects. For young people, applications such as SnapChat or Instagram have taken on a central role in personalized AR.…”

Section: Literature Reviewmentioning

confidence: 99%

Use of Beauty Applications and Ar Beauty Filters Among Young People: Trends and Challenges

Šiđanin,

Milić,

Mitrović

et al. 2023

19th International Scientific Conference on Industrial Systems

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Beauty applications and augmented reality beauty filters are widely used on social media platforms. These filters detect and transform facial features by overlaying digital masks on moving faces. In addition to beauty applications that are used for retroactive photo editing, augmented reality beauty filters adapt to facial features in real-time, resulting in a unique digital beautifying process. This quantitative study explores how the use of beauty applications and the use of AR beauty filters impacts young people's perception of themselves, and whether their use affects the self-confidence and mental health of young people. It is based on an online survey that was conducted on a sample of 232 respondents from the category of young people (i.e. Millennials and Gen Z). For that purpose, this paper provides a relevant literature review on the attitude of young people toward trends that are imposed through social networks. The research results showed that more than 70% of respondents use ARB filters and applications to beautify their photos. Young people are largely satisfied with their appearance and more than half of them do not succumb to trends imposed by social networks. However, they notice that an increasing number of people strive for imposed ideals of beauty, which affects their self-confidence.

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Section: Literature Reviewmentioning

confidence: 99%

Use of Beauty Applications and Ar Beauty Filters Among Young People: Trends and Challenges

Šiđanin,

Milić,

Mitrović

et al. 2023

19th International Scientific Conference on Industrial Systems

View full text Add to dashboard Cite

show abstract

“…The possibility of experiencing these transformations transcends the physical location of the users as all is needed is a smartphone with an Internet connection, making AR face filters a form of post-Internet art (4). The COVID-19 pandemic has represented a turning point for the general acceptance of AR filters as an effective form of art (23), giving filter creators an essential responsibility in shaping the cultural and societal impact of this technology.…”

Section: Introductionmentioning

confidence: 99%

OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters

Riccio¹,

Psomas²,

Galati³

et al. 2022

Preprint

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Augmented Reality or AR filters on selfies have become very popular on social media platforms for a variety of applications, including marketing, entertainment and aesthetics. Given the wide adoption of AR face filters and the importance of faces in our social structures and relations, there is increased interest by the scientific community to analyze the impact of such filters from a psychological, artistic and sociological perspective. However, there are few quantitative analyses in this area mainly due to a lack of publicly available datasets of facial images with applied AR filters. The proprietary, close nature of most social media platforms does not allow users, scientists and practitioners to access the code and the details of the available AR face filters. Scraping faces from these platforms to collect data is ethically unacceptable and should, therefore, be avoided in research. In this paper, we present OpenFilter, a flexible framework to apply AR filters available in social media platforms on existing large collections of human faces. Moreover, we share FairBeauty and B-LFW, two beautified versions of the publicly available FairFace and LFW datasets and we outline insights derived from the analysis of these beautified datasets.

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Meta’s artistic turn: AR face filters, platform art, and the actually existing metaverse

Bozzi

2024

Information, Communication & Society

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Face Filters as Augmented Reality Art on Social Media

Cited by 5 publications

References 10 publications

Use of Beauty Applications and Ar Beauty Filters Among Young People: Trends and Challenges

Use of Beauty Applications and Ar Beauty Filters Among Young People: Trends and Challenges

OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters

Meta’s artistic turn: AR face filters, platform art, and the actually existing metaverse

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