TY  - BOOK
AU  - Manilitphone Thephavanh
TI  - Emotion Analysis / 
PY  - 2019///
CY  - Bandar Seri Begawan
PB  -  Universiti Teknologi Brunei , 
KW  - Report
KW  - Universiti Teknologi Brunei
KW  - Emotions
KW  - Research
KW  - Psychological aspects
N1  - Report submitted for the degree of BCs in Creative Multimedia Universiti Teknologi Brunei; Abstract

Emotion analysis is useful for many applications dealing with human emotions. A lot of time consuming in order to find the best practice and algorithm for emotion classification, detection and prediction because the analysis can be done in several techniques such as using Ekman's Facial Action Coding System (FACS), Geometric Feature, MPEG 4, facial landmarks detection by Dlib, etc. However, it's hard to achieve high accurate result with certain database and learning tools. This analysis purpose to explore and experiment various of machine learning techniques that can outcome with accuracy results for each technique in a certain condition. By using the Extended Cohn-Kanade Dataset (CK+) with appropriate data mining tool will help to analyze universal of human emotions and result with reasonable accuracy. This analysis focusing on facial landmarks features in order to classify different types of emotion; Includes bibliographical references
ER  -