Real time human facial expression detection
Human Facial Expression detection is an important scope in research with regards to human computer interaction. In this project, Convolutional Neural Networks (CNN) is utilized to detect facial expressions, where the model should be able to identify seven emotions (happy, sad, disgust, angry, surpri...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/149372 |
| _version_ | 1826110482532007936 |
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| author | Chong, Grace Kai Xin |
| author2 | Wang Han |
| author_facet | Wang Han Chong, Grace Kai Xin |
| author_sort | Chong, Grace Kai Xin |
| collection | NTU |
| description | Human Facial Expression detection is an important scope in research with regards to human computer interaction. In this project, Convolutional Neural Networks (CNN) is utilized to detect facial expressions, where the model should be able to identify seven emotions (happy, sad, disgust, angry, surprised, fear, neutral) based on an input image or a live webcam feed. CNN of different depths were trained using grayscale images from the Kaggle website using Tensorflow and Keras. Using different networks while tuning different hyperparameters were explored and their effects on the accuracy of predicting the correct output. State-of-the-Art models were also taken inspiration from and used for this task. |
| first_indexed | 2024-10-01T02:35:10Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/149372 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:35:10Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1493722023-07-07T18:12:35Z Real time human facial expression detection Chong, Grace Kai Xin Wang Han School of Electrical and Electronic Engineering HW@ntu.edu.sg Engineering::Electrical and electronic engineering Human Facial Expression detection is an important scope in research with regards to human computer interaction. In this project, Convolutional Neural Networks (CNN) is utilized to detect facial expressions, where the model should be able to identify seven emotions (happy, sad, disgust, angry, surprised, fear, neutral) based on an input image or a live webcam feed. CNN of different depths were trained using grayscale images from the Kaggle website using Tensorflow and Keras. Using different networks while tuning different hyperparameters were explored and their effects on the accuracy of predicting the correct output. State-of-the-Art models were also taken inspiration from and used for this task. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-09T02:59:32Z 2021-06-09T02:59:32Z 2021 Final Year Project (FYP) Chong, G. K. X. (2021). Real time human facial expression detection. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149372 https://hdl.handle.net/10356/149372 en A1155-201 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Chong, Grace Kai Xin Real time human facial expression detection |
| title | Real time human facial expression detection |
| title_full | Real time human facial expression detection |
| title_fullStr | Real time human facial expression detection |
| title_full_unstemmed | Real time human facial expression detection |
| title_short | Real time human facial expression detection |
| title_sort | real time human facial expression detection |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/149372 |
| work_keys_str_mv | AT chonggracekaixin realtimehumanfacialexpressiondetection |