Face swapping based on machine learning
Out of the increasing demand of internet security and entertainment, the face swapping technology attracts great attention in both academic area and commercial companies. This dissertation mainly construct a face swapping system. Firstly use Histogram of Oriented Gradient (HOG) to detect the face in...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/150319 |
| _version_ | 1811687085584678912 |
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| author | Zhou, Suxi |
| author2 | Jiang Xudong |
| author_facet | Jiang Xudong Zhou, Suxi |
| author_sort | Zhou, Suxi |
| collection | NTU |
| description | Out of the increasing demand of internet security and entertainment, the face swapping technology attracts great attention in both academic area and commercial companies. This dissertation mainly construct a face swapping system. Firstly use Histogram of Oriented Gradient (HOG) to detect the face in a given image, and use training data to generate a prediction model based on the gradient boosting decision tree (GBDT) algorithm to extract the coordinates of 81 feature points of facial features and facial contours; Then train the Multi-Layer Perceptron (MLP) classifier to predict the gender and race of the face to be recognized and find the reference face image of the same gender race. Lastly, use the extracted feature point coordinates to exchange the facial features of the target face image and the reference face image. |
| first_indexed | 2024-10-01T05:10:42Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/150319 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:10:42Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1503192023-07-04T16:15:04Z Face swapping based on machine learning Zhou, Suxi Jiang Xudong School of Electrical and Electronic Engineering EXDJiang@ntu.edu.sg Engineering::Computer science and engineering::Information systems::Information systems applications Engineering::Electrical and electronic engineering Out of the increasing demand of internet security and entertainment, the face swapping technology attracts great attention in both academic area and commercial companies. This dissertation mainly construct a face swapping system. Firstly use Histogram of Oriented Gradient (HOG) to detect the face in a given image, and use training data to generate a prediction model based on the gradient boosting decision tree (GBDT) algorithm to extract the coordinates of 81 feature points of facial features and facial contours; Then train the Multi-Layer Perceptron (MLP) classifier to predict the gender and race of the face to be recognized and find the reference face image of the same gender race. Lastly, use the extracted feature point coordinates to exchange the facial features of the target face image and the reference face image. Master of Science (Signal Processing) 2021-06-08T12:41:32Z 2021-06-08T12:41:32Z 2021 Thesis-Master by Coursework Zhou, S. (2021). Face swapping based on machine learning. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150319 https://hdl.handle.net/10356/150319 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Information systems::Information systems applications Engineering::Electrical and electronic engineering Zhou, Suxi Face swapping based on machine learning |
| title | Face swapping based on machine learning |
| title_full | Face swapping based on machine learning |
| title_fullStr | Face swapping based on machine learning |
| title_full_unstemmed | Face swapping based on machine learning |
| title_short | Face swapping based on machine learning |
| title_sort | face swapping based on machine learning |
| topic | Engineering::Computer science and engineering::Information systems::Information systems applications Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/150319 |
| work_keys_str_mv | AT zhousuxi faceswappingbasedonmachinelearning |