Affect recognition for handheld devices
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...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2013
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| Online Access: | https://animorepository.dlsu.edu.ph/etd_honors/372 |
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| Institution: | De La Salle University |
| Language: | English |
| 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%. |
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