Emotion detection from frontal facial image
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013.
| Hlavní autor: | |
|---|---|
| Další autoři: | |
| Médium: | Diplomová práce |
| Jazyk: | English |
| Vydáno: |
BRAC University
2014
|
| Témata: | |
| On-line přístup: | http://hdl.handle.net/10361/2931 |
| id |
10361-2931 |
|---|---|
| record_format |
dspace |
| spelling |
10361-29312022-01-26T10:10:29Z Emotion detection from frontal facial image Hussain, Sakib Ali, Abu Mohammad Hammad Department of Computer Science and Engineering, BRAC University Emotions Color Model Feature extraction Viola- jones Neural Network Emotion recognition Computer science and engineering This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013. Cataloged from PDF version of thesis report. Includes bibliographical references (page 28). Emotion recognition from facial images is a very active re-search topic in human computer interaction (HCI). In order to detect Emotion from an image I have used frontal view facial images. If computers can understand more of human emotion, we can make better systems to reduce the gap of human computer interaction .To handle the emotion recognition problem from arbitrary view facial images. The facial region and others part of the body have been segmented from the complex environment based on skin color model. Thus, in this paper I showed some differences between different color models that are used to implement the system and which color model can be used where. Another aspect is to extract facial parts from the face. And for that I have used Viola - Jones algorithm to detect the eye and lips region from a face and then by the help of neural network I have detected emotion from those features. From the positioning of mouth and eyes I tried to detect emotion of a face. In this research I will propose an effective way to detect neutral, happy, sad and surprise these four emotions from frontal facial image of Human Being. Sakib Hussain B. Computer Science and Engineering 2014-02-09T14:45:53Z 2014-02-09T14:45:53Z 2013 2013-10 Thesis ID 09101004 http://hdl.handle.net/10361/2931 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 28 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Emotions Color Model Feature extraction Viola- jones Neural Network Emotion recognition Computer science and engineering |
| spellingShingle |
Emotions Color Model Feature extraction Viola- jones Neural Network Emotion recognition Computer science and engineering Hussain, Sakib Emotion detection from frontal facial image |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013. |
| author2 |
Ali, Abu Mohammad Hammad |
| author_facet |
Ali, Abu Mohammad Hammad Hussain, Sakib |
| format |
Thesis |
| author |
Hussain, Sakib |
| author_sort |
Hussain, Sakib |
| title |
Emotion detection from frontal facial image |
| title_short |
Emotion detection from frontal facial image |
| title_full |
Emotion detection from frontal facial image |
| title_fullStr |
Emotion detection from frontal facial image |
| title_full_unstemmed |
Emotion detection from frontal facial image |
| title_sort |
emotion detection from frontal facial image |
| publisher |
BRAC University |
| publishDate |
2014 |
| url |
http://hdl.handle.net/10361/2931 |
| work_keys_str_mv |
AT hussainsakib emotiondetectionfromfrontalfacialimage |
| _version_ |
1814307833694388224 |