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
Accession Number
TU18554
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
1v. various foliations : illustrations (some colored) ; 28 cm.
Recommended Citation
Go, G. O., Ling, G. C., & Uy, T. T. (2013). Affect recognition for handheld devices. Retrieved from https://animorepository.dlsu.edu.ph/etd_honors/372
