Citation: Proceedings of the 2020 International Conference on Research in Management & Technovation, Shivani Agarwal, Darrell Norman Burrell, Vijender Kumar Solanki (eds). ACSIS, Vol. 24, pages 115–118 (2020)
Abstract. In this paper we describe a methodology and an algorithm to estimate the real-time age, gender, and emotion of a human by analyzing of face images on a webcam. Here we discuss the CNN based architecture to design a real-time model. Emotion, gender and age detection of facial images in webcam play an important role in many applications like forensics, security control, data analysis,video observation and human-computer interaction. In this paper we present some method \& techniques such as PCA,LBP, SVM, VIOLA-JONES, HOG which will directly or indirectly used to recognize human emotion, gender and age detection in various conditions
- Md. Jashim Uddin, Dr. Paresh Chandra Barman, Khandaker Takdir Ahmed S.M. Abdur Rahim , Abu Rumman Refat , Md Abdullah-Al- Imran6 "A Convolutional Neural Network for Real-time Face Detection and Emotion & Gender Classification" IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
- Thakshila R. Kalansuriya and Anuja T. Dharmaratne,"Neural Network based Age and Gender Classification for Facial Images" International Journal on Advances in ICT for Emerging Regions
- M. R. Dileepa and Ajit Dantib "Human Age and Gender Prediction Based on Neural Networks and Three Sigma Control Limits" ISSN: 0883-9514 (Print) 1087- 6545 (Online) Journal homepage: http://www.tandfonline.com/loi/uaai20
- 2018-Sepidehsadat Hosseini, Seok Hee Lee, Hyuk Jin Kwon, Hyung Il Koo Nam Ik Cho, “Age and Gender Classification Using Wide Convolutional Neural Network and Gabor Filter”, IEEE2018.
- Imane Lasri, Anouar Riad Solh Mourad E Belkacemi, “Facial Emotion Recognition of Students using Convolutional Neural Network”, IEEE- 2019.
- Rajesh Kumar G A, Ravi Kant Kumar Goutam Sanyal, “Facial Emotion Analysis using Deep Convolutional Neural Network”,2017 International Conference on Signal Processing and Communication (ICSPC). http://dx.doi.org/10.1109/ cspc.2017.8305872, Pg.No.- 369 to374.
- Md Abdullah-Al-Imran “A Convolutional Neural Network for Real-time Face Detection and Emotion & Gender Classification’’ e-ISSN: 2278-2834, p- ISSN: 2278-8735. Volume15, Issue 3, Ser. I (May - June2020), PP 37-46.
- S L Happy and Aurobinda Routray“Automatic Facial Expression Recognition Using Features of Salient Facial Patches’’http://dx.doi.org/10.1109/ TAFFC. 2014. 2386334 https://rb.gy/9m5dt2.
- Ramin Azarmehr, Robert Laganiere, Won-Sook Lee Real-time Embedded Age and Gender Classification in Unconstrained Video h ttps://rb.gy/pnvd2n.
- Jang-Hee Yoo, So-Hee Park, and Yongjin Lee “Real-Time Ageand Gender Estimation from Face Image” ISBN: 978-0-6480147-3-7.
- Octavio Arriaga1 and Matias Valdenegro-Toro and Paul G. Pl¨oger Real-time Convolutional Neural Networks for emotion and gender classification.”
- Eran Eidinger, Roee Enbar, Tal Hassner “Age and Gender Estimation of Unfiltered Faces’’
- Ajit P. Gosavi, S. R. Khot “Facial Expression Recognition Using Principal Component Analysis” ISSN: 2231-2307, Volume-3, Issue-4, September 2013
- Sidharth Nair, Dipesh Nair, “Detection of Gender, Age and Emotion of a Human Image using Facial Features” e-ISSN: 2395-0056 www.irjet.netp- ISSN: 2395-0072
- Rekha N, Dr.M.Z.Kurian "Face Detection in Real Time Based on HOG" international journal of advanced Research in computer engineering & tchnology volume 3 issue 4,april2014 ISSN:2278-1323
- Tanner Gilligan, Baris Akis Emotion AI, Real-Time Emotion Detection using CNN " http://web.stanford.edu/class/cs231a/prev_projects_2016/e motion-ai-real.pdf