Published 2018
“…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion
detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial
expression.Therefore,the aims of this study are threefold which are to enhance the
algorithm to
detect spontaneous emotion,to develop spontaneous facial
expression database and to verify the
algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the
expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.
Basically,the performance of the system is indicated by emotion
detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial
expression (63.28%) compared to posed facial
expression (51.46%).The verification even better for positive emotion with 71.02%
detection rate compared to 48.09% for negative emotion
detection rate.Finally,overall
detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
Get full text
Get full text
Get full text
Get full text
Thesis
