PENERAPAN MULTICLASS SUPPORT VECTOR MACHINES UNTUK PENGENALAN EKSPRESI WAJAH SECARA REAL TIME

RIFKY, HASBY and Samsuryadi, Samsuryadi (2019) PENERAPAN MULTICLASS SUPPORT VECTOR MACHINES UNTUK PENGENALAN EKSPRESI WAJAH SECARA REAL TIME. Undergraduate thesis, Sriwijaya University.

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Abstract

The recognition of facial expressions using a smartphone is one of the computer vision problems, due to the lack of resources that smartphone compared to desktops. However, smartphones are more widely used than desktops. In this research, smartphone is used to recognize facial expressions in real time that integrated with a server. Face area detected on smartphones using Viola Jones, and sent to the server to place Active Shape Model (ASM) landmarks on the face. The move of landmark points on the face in each frame is classified using Support Vector Machines (SVM) to determine the type of expression. The expressions classified in this study were sad, happy, and surprised. This experiment was able to produce average precision about 0.685, recall about 0.667, F_1 about 0.649, and accuracy about 75% with facial expressions data of 30 expressions that taken directly on the subject. While testing using a dataset from Extended Cohn-Kanade (CK+) of 42 expressions produces average precision about 0.814, recall about 0.809, F_1 about 0.810 and accuracy about 86.6%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Teknik Informatika, Jaringan Syaraf Tiruan
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 3856 not found.
Date Deposited:	31 Dec 2019 03:13
Last Modified:	31 Dec 2019 03:13
URI:	http://repository.unsri.ac.id/id/eprint/22729

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