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https://hdl.handle.net/10356/76147
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DC Field | Value | Language |
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dc.contributor.author | Koh, Melvyn Nguan Theng | |
dc.date.accessioned | 2018-11-20T08:46:17Z | |
dc.date.available | 2018-11-20T08:46:17Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | http://hdl.handle.net/10356/76147 | |
dc.description.abstract | Deep learning dominates the field of computer vision in recent years and in every few weeks a new deep learning technology takes over the other. Herein, convolutional neural network (CNN) is applied in this project. Detecting facial expressions have been a very fast-growing topic in the field of computer vision as facial expressions are seen as a significant role in human communication and behavioural analysis. Ever since Paul Ekman devised the Facial Action Coding System (FACS) to detect a human facial feature and model the facial behaviours, many scientists are inspired to conduct psychological research on detecting real emotions of a person. Therefore, this has in turn inspired computer scientists to conduct tremendous active research in this field – finding the most accurate and fast models to detecting the true emotion of a person with a camera. This involves using Extended Cohn-Kanade (CK+) and FER2013 datasets. This project aims to build a Real-Time Emotion Detection application that detects seven emotions namely – Anger, Disgust, Fear, Happy, Sad, Surprise and Neutral. The software application is written in Python programming language with OpenCV for processing images and videos. CNN-based approach is done with Google’s Tensorflow machine-learning library to construct the trained model. Lastly, Keras is used as the high-level neural networks API (application programming interface) that runs on top of Tensorflow. The model is trained and evaluated on the FER2013 and CK+ datasets. | en_US |
dc.format.extent | 47 p. | en_US |
dc.language.iso | en | en_US |
dc.rights | Nanyang Technological University | |
dc.subject | DRNTU::Engineering::Computer science and engineering | en_US |
dc.title | Real-time emotion detection | en_US |
dc.type | Final Year Project (FYP) | en_US |
dc.contributor.supervisor | Althea Liang Qianhui | en_US |
dc.contributor.school | School of Computer Science and Engineering | en_US |
dc.description.degree | Bachelor of Engineering (Computer Engineering) | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | restricted | - |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
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Melvyn_Koh_Nguan_Theng_Report.pdf Restricted Access | Final Year Project Report | 3.34 MB | Adobe PDF | View/Open |
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