Facial feature comparison between biological relatives
Facial feature recognition techniques that allow fast and efficient face detection have gained popularity in recent years. Based on the concepts of Viola-Jones robust real-time face detection, this project aims to find facial features that are able to determine if two individuals are related. In...
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sg-ntu-dr.10356-676632023-07-07T16:09:05Z Facial feature comparison between biological relatives Teoh, Geraldine Shi En Anamitra Makur School of Electrical and Electronic Engineering DRNTU::Engineering Facial feature recognition techniques that allow fast and efficient face detection have gained popularity in recent years. Based on the concepts of Viola-Jones robust real-time face detection, this project aims to find facial features that are able to determine if two individuals are related. In this project, images sets of related and unrelated individuals was collected. Facial features such as the nose and eyes were extracted from the image and used for analysis. Other facial features such as the ratios between facial landmarks were also used for analysis. Methods of comparison were used to determine the effectiveness of the facial features in differentiating related and unrelated individuals. In order to differentiate related and unrelated pairs, a threshold value had to be determined for each facial feature. Since not all facial features are equally effective, a weightage was allocated to each facial feature according to their effectiveness in differentiating related and unrelated individuals. The experimental results showed that using a combination of certain facial features with the appropriate threshold values and weightages, related and unrelated individuals were able to be differentiated most of the time. However, more extensive research should be done on a larger sample size to give more substantial results. Bachelor of Engineering 2016-05-19T02:32:49Z 2016-05-19T02:32:49Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67663 en Nanyang Technological University 85 p. application/pdf |
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DRNTU::Engineering Teoh, Geraldine Shi En Facial feature comparison between biological relatives |
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Facial feature recognition techniques that allow fast and efficient face detection have gained popularity in recent years. Based on the concepts of Viola-Jones robust real-time face detection, this project aims to find facial features that are able to determine if two individuals are related.
In this project, images sets of related and unrelated individuals was collected. Facial features such as the nose and eyes were extracted from the image and used for analysis. Other facial features such as the ratios between facial landmarks were also used for analysis. Methods of comparison were used to determine the effectiveness of the facial features in differentiating related and unrelated individuals. In order to differentiate related and unrelated pairs, a threshold value had to be determined for each facial feature. Since not all facial features are equally effective, a weightage was allocated to each facial feature according to their effectiveness in differentiating related and unrelated individuals.
The experimental results showed that using a combination of certain facial features with the appropriate threshold values and weightages, related and unrelated individuals were able to be differentiated most of the time. However, more extensive research should be done on a larger sample size to give more substantial results. |
author2 |
Anamitra Makur |
author_facet |
Anamitra Makur Teoh, Geraldine Shi En |
format |
Final Year Project |
author |
Teoh, Geraldine Shi En |
author_sort |
Teoh, Geraldine Shi En |
title |
Facial feature comparison between biological relatives |
title_short |
Facial feature comparison between biological relatives |
title_full |
Facial feature comparison between biological relatives |
title_fullStr |
Facial feature comparison between biological relatives |
title_full_unstemmed |
Facial feature comparison between biological relatives |
title_sort |
facial feature comparison between biological relatives |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/67663 |
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1772827413578776576 |