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
