Earticle

초록

영어

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called ‘autoblur’, which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source ‘Face Recognition’ which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.

목차

Abstract
1. INTRODUCTION
2. RELATED WORK
2.1 Hello Mirror Project using Openface
2.2 Application Zao using DeepFake
3. OUR METHOD
3.1 Face Registration (Training Data Learning)
3.2 Automatic Image Conversion (Editing Test Data)
4. EXPERIMENTAL RESULTS
5. CONCLUSION
ACKNOWLEDGEMENTThis work was supported by a research
REFERENCES

키워드

저자

• Hyeon-Dham Yoon [ Undergraduated Student, Major of Visual Communication Design, Seoul Women’s University ]
• Seong-Yong Ohm [ Professor, Department of Software Convergence, Seoul Women’s University ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Culture Technology(IJACT)

• 간기

  계간

• pISSN

  2288-7202

• eISSN

  2288-7318

• 수록기간

  2013~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 600 DDC 700