Biometric modals for visual surveillience applications
Video surveillance applications are increasingly developed using the biometric modals of human being such as face features, face postures and others soft biometric modals i.e. skin, hair and etc. Many developments have to be done on the human recognition such as estimation of age and gender, consist...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2010
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| Online Access: | http://hdl.handle.net/10356/20721 |
| _version_ | 1826109934130954240 |
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| author | Wai, Mon Kyaw |
| author2 | Teoh Eam Khwang |
| author_facet | Teoh Eam Khwang Wai, Mon Kyaw |
| author_sort | Wai, Mon Kyaw |
| collection | NTU |
| description | Video surveillance applications are increasingly developed using the biometric modals of human being such as face features, face postures and others soft biometric modals i.e. skin, hair and etc. Many developments have to be done on the human recognition such as estimation of age and gender, consistent human tracking and learning of movement with behavior.
The main focus of this project is to develop the system to recognize similar people in
video images using facial biometric features. Firstly, segmentation of the skin is to reject as much “non-face” of the image as possible. Conventionally, the face images are not always in straight eyes aligned position owing to the dependency of situation the images are taken and varying face postures. To generalize the face postures of all the test images, face alignment process using the coordinates of two eyes position has to be done as a pre processing.The comprehensive objective of this project is to focus on classification of family
members from non family members using Gabor facial features of each family and
select the classifier with best performance using the AdaBoost feature selection
algorithm which is statistically robust, computationally efficient and global image
processing algorithm. |
| first_indexed | 2024-10-01T02:26:32Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/20721 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:26:32Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | ntu-10356/207212023-07-07T15:48:53Z Biometric modals for visual surveillience applications Wai, Mon Kyaw Teoh Eam Khwang School of Electrical and Electronic Engineering A*STAR Institute for Infocomm Research DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics Video surveillance applications are increasingly developed using the biometric modals of human being such as face features, face postures and others soft biometric modals i.e. skin, hair and etc. Many developments have to be done on the human recognition such as estimation of age and gender, consistent human tracking and learning of movement with behavior. The main focus of this project is to develop the system to recognize similar people in video images using facial biometric features. Firstly, segmentation of the skin is to reject as much “non-face” of the image as possible. Conventionally, the face images are not always in straight eyes aligned position owing to the dependency of situation the images are taken and varying face postures. To generalize the face postures of all the test images, face alignment process using the coordinates of two eyes position has to be done as a pre processing.The comprehensive objective of this project is to focus on classification of family members from non family members using Gabor facial features of each family and select the classifier with best performance using the AdaBoost feature selection algorithm which is statistically robust, computationally efficient and global image processing algorithm. Bachelor of Engineering 2010-01-06T06:29:18Z 2010-01-06T06:29:18Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/20721 en Nanyang Technological University 125 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics Wai, Mon Kyaw Biometric modals for visual surveillience applications |
| title | Biometric modals for visual surveillience applications |
| title_full | Biometric modals for visual surveillience applications |
| title_fullStr | Biometric modals for visual surveillience applications |
| title_full_unstemmed | Biometric modals for visual surveillience applications |
| title_short | Biometric modals for visual surveillience applications |
| title_sort | biometric modals for visual surveillience applications |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics |
| url | http://hdl.handle.net/10356/20721 |
| work_keys_str_mv | AT waimonkyaw biometricmodalsforvisualsurveillienceapplications |