@inproceedings{d4d18a551b114cfca651880a18cb365c,
title = "Notice of Retraction: Human emotional states modeling by Hidden Markov Model",
abstract = "This paper presents an attempt of using Hidden Markov Model to model the high level emotions (such as, encouraging, interest, unsure, disagreeing and discouraging) through low level facial expressions (such as, happy, sad, surprise and neutral). The rationale behind using HMM is that the HMM models human brain as human emotion is quite complex, naturally a human instinct contain hidden layer as well (like sub conscious mind). In addition, Markov state chain property is good to model human emotion as our emotion is also through our mind state that it is always dependent on our previous state of our emotion and current event will end up our current emotion state. Our proposed work is to develop an emotion indexer acting as a higher level analysis to interpret more advanced emotional states out of the basic emotions.",
keywords = "Emotion, Facial Expressions, Hidden Markov Model",
author = "Teoh, {Teik Toe} and Cho, {Siu Yeung}",
year = "2011",
doi = "10.1109/ICNC.2011.6022189",
language = "English",
isbn = "9781424499533",
series = "Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011",
publisher = "IEEE Computer Society",
pages = "908--912",
booktitle = "Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011",
address = "United States",
note = "2011 7th International Conference on Natural Computation, ICNC 2011 ; Conference date: 26-07-2011 Through 28-07-2011",
}