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http://dx.doi.org/10.9728/dcs.2018.19.7.1349

Implementation of Multi Channel Network Platform based Augmented Reality Facial Emotion Sticker using Deep Learning  

Kim, Dae-Jin (Research Institute for Image & Cultural Contents, Dongguk University)
Publication Information
Journal of Digital Contents Society / v.19, no.7, 2018 , pp. 1349-1355 More about this Journal
Abstract
Recently, a variety of contents services over the internet are becoming popular, among which MCN(Multi Channel Network) platform services have become popular with the generalization of smart phones. The MCN platform is based on streaming, and various factors are added to improve the service. Among them, augmented reality sticker service using face recognition is widely used. In this paper, we implemented the MCN platform that masks the augmented reality sticker on the face through facial emotion recognition in order to further increase the interest factor. We analyzed seven facial emotions using deep learning technology for facial emotion recognition, and applied the emotional sticker to the face based on it. To implement the proposed MCN platform, emotional stickers were applied to the clients and various servers that can stream the servers were designed.
Keywords
Deep Learning; Facial Emotion Recognition; Sticker; Augmented Reality; MCN(Multi Channel Network) Platform;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Dae-Jin Kim, "Implementation of One-Pserson Media Live System in Closed network Environment," Journal of Digital contents Society, Vol. 18, No. 1, pp. 1-4, 2017   DOI
2 Luis Rodriguez-Gil, Pablo Orduna, Javier Garcia-Zubia, Diego Lopez-de-lpina, "Interactive live-streaming technologies and approaches for web-based applications," Multimedia Tools and Applications, Vol. 77, pp. 6471-6502, 2018   DOI
3 Jianwei Zhang, Xinchang Zhang, Chunling Yang, "Towards the multi-request mechanism in pull-based peer-to-peer live streaming systems," Computer Networks, Vol. 138, pp. 77-89, 2018   DOI
4 Yi Sun1, Xiaogang Wang, Xiaoou Tang, "Deep Learning Face Representation from Predicting 10,000 Classes," Computer Vision and Pattern Recognition(CVPR), pp. 1891-1898, 2014
5 Donghee Shin, "Empathy and embodied experience in virtual environment: To what extent can virtual reality stimulate empathy and embodied experience?", Computers in Human Behavior, Vol. 78, pp. 64-73, 2018   DOI
6 Mobitalk project [Internet]. Available: http://www.maneullab.com/.
7 Rajeev Ranjan, Swami Sankaranarayanan, Ankan Bansal, Navaneeth Bodla, Jun-Cheng Chen, Vishal M. Patel, Carlos D. Castillo, Rama Chellappa, "Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans", IEEE Signal Processing Magazine, Vol. 35, pp. 66-83, 2018   DOI
8 Facial Express Recognition Challenge [Internet]. https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data
9 Dae-Jin Kim, "Implementation of Real-time Video Surveillance System based on Multi-Screen in Mobile-phone Environment," Journal of Digital contents Society, Vol. 18, No. 6, pp. 1009-1015, 2017