Human age estimation based on face images
Nowadays, there are forensic artists who are able to draw out images of people and at the same time make realistic age progression. There are Swedish alcohol salespersons that have a professional skill in age recognition. But the question is can the computer perform the same function like the gro...
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| 主要作者: | |
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| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
2011
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| 主題: | |
| 在線閱讀: | http://hdl.handle.net/10356/44926 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | Nowadays, there are forensic artists who are able to draw out images of
people and at the same time make realistic age progression. There are
Swedish alcohol salespersons that have a professional skill in age recognition.
But the question is can the computer perform the same function like the group
of people mentioned?
In this project, the student had developed a program for the computer to
recognize the age group of the user via a webcam. The student made used
of Haar-like features from OpenCV for face detection via a webcam. Upon the
detection of face, the image was cropped and thereafter the features of the
face will be extracted. Feature extraction was done using Gabor filters and
local binary pattern.
After the extraction of features, the program will classify the result into 4
categories. They are “Children”, “Teens”, “Adults” and “Senior Adults”. In this
project, the student had trained adaboost and sets of results were obtained.
The results obtained from Adabooost were thereafter applied to Error
Correction Output Coding for the final prediction of the age group. The
purpose of Error Correction Output Coding was to convert multi class problem
to a two-class problem. |
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