Automated Real Time Emotion Recognition Using Facial Expression Analysis
Public Deposited- Resource Type
- Creator
- Abstract
The focus of this study is on computer automated perception of human emotion. We explore the use of Fisherfaces for the recognition of human emotion in facial images. We train a multitude of Fisherface models and evaluate their performance against an independent test set. We build and test a compound hierarchical system that attempts to interpret human emotion in real time using face detection and tracking algorithms in conjunction with our facial expression analysis methodology. Our results indicate that Fisherfaces can be useful in predicting emotion based on content retrieved from facial images. We note that, with this approach, some emotions are more easily predicted than others. We also suggest that a compound hierarchical model is more effective than a single stand-alone Fisherface model.
- Subject
- Language
- Publisher
- Thesis Degree Level
- Thesis Degree Name
- Thesis Degree Discipline
- Identifier
- Rights Notes
Copyright © 2016 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
- Date Created
- 2016
Relations
- In Collection:
Items
Thumbnail | Title | Date Uploaded | Visibility | Actions |
---|---|---|---|---|
fratesi-automatedrealtimeemotionrecognitionusingfacial.pdf | 2023-05-04 | Public | Download |