Affect recognition for handheld devices

Date of Publication

2013

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Science

College

College of Computer Studies

Department/Unit

Computer Science

Honor/Award

Awarded as best thesis, 2013

Thesis Adviser

Jocelynn W. Cu

Defense Panel Chair

Ethel Chua Joy Ong

Defense Panel Member

Joel P. Ilao
Ralph Vincent J. Regalado

Abstract/Summary

This study focuses on the development of an affect recognition system for Android handheld devices following the client-server framework, where data acquisition and display of outputs are done on the handheld device while feature extraction and classification are dine on the Java application server running on a computer. Data acquisition is done through a math game where the subject is recorded while playing the game. Motion history images (MHI) and edge orientation histogram (EOH) were used to represent the face. Categorical labels " Interest, Amusement and Neutral " are the emotions used and these are classified through a decision tree model following the C4.5 or J48 algorithm with an accuracy score of 89% and 94%.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU18554

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1v. various foliations : illustrations (some colored) ; 28 cm.

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