TY - GEN
T1 - Enhancing facial component analysis
AU - Pebiana, Siska
AU - Basaruddin, T.
AU - Widyanto, M. Rahmat
AU - Liliana, Dewi Yanti
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/1/10
Y1 - 2019/1/10
N2 - Capturing non-verbal information from a face is the most important phase in emotion recognition through facial expression. In order to do that, it needs to find suitable features extraction method that could help to figure out the meaning from the given face. Inspired by Liliana Dewi[1] that used a geometric feature for analyzing facial component with a good result accuracy around 98.59%. So this paper tries to improve that method in order to enhance the result of facial components analysis. This study use Hellen dataset to retrain the Active Appearance Model (AAM), add image preprocessing like image enhancement, use other geometric features and Fuzzy Rule-Based System for extract the feature on extended Cohn Kanade (CK+) dataset. The result of this research gives better in recognizing facial components than previous work with accuracy around 99.36%.
AB - Capturing non-verbal information from a face is the most important phase in emotion recognition through facial expression. In order to do that, it needs to find suitable features extraction method that could help to figure out the meaning from the given face. Inspired by Liliana Dewi[1] that used a geometric feature for analyzing facial component with a good result accuracy around 98.59%. So this paper tries to improve that method in order to enhance the result of facial components analysis. This study use Hellen dataset to retrain the Active Appearance Model (AAM), add image preprocessing like image enhancement, use other geometric features and Fuzzy Rule-Based System for extract the feature on extended Cohn Kanade (CK+) dataset. The result of this research gives better in recognizing facial components than previous work with accuracy around 99.36%.
KW - Aam
KW - Active appearance model
KW - Facial component analysis
KW - Fuzzy rule based system
UR - http://www.scopus.com/inward/record.url?scp=85063571947&partnerID=8YFLogxK
U2 - 10.1145/3305160.3305174
DO - 10.1145/3305160.3305174
M3 - Conference contribution
AN - SCOPUS:85063571947
T3 - ACM International Conference Proceeding Series
SP - 175
EP - 179
BT - Proceedings of the 2019 2nd International Conference on Software Engineering and Information Management, ICSIM 2019 - Workshop 2019 2nd International Conference on Big Data and Smart Computing, ICBDSC 2019
PB - Association for Computing Machinery
T2 - 2nd International Conference on Software Engineering and Information Management, ICSIM 2019 - and its Workshop 2019 2nd International Conference on Big Data and Smart Computing, ICBDSC 2019
Y2 - 10 January 2019 through 13 January 2019
ER -