Real-time face detection and recognition
Real-time face detection (RTFD) and recognition is used widely in many areas from tagging faces on Facebook, custom services at airports and to unlocking phones through a face recognition application. The main functionality involves verifying the identity of a person and in doing so, applying that r...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2014
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| Online Access: | http://hdl.handle.net/10356/58995 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Real-time face detection (RTFD) and recognition is used widely in many areas from tagging faces on Facebook, custom services at airports and to unlocking phones through a face recognition application. The main functionality involves verifying the identity of a person and in doing so, applying that result in various other applications.. In this report, we study various face detection and recognition techniques and use an appropriate one to develop a program that can perform real-time face detection and recognition.
This report will compare the pros and cons of various methods of RTFD and recognition. Some of the current methods that are used for RTFD are Haarcascade Classifier, Colour Extraction and Motion Detection. For recognition, they are Correlation, Eigenfaces and Fisherfaces. The most suitable method will be selected and used for this project.
As this is a real time system, time factor plays an important part for selection of methods. After comparison, Haarcascade Classifier will be used for real time face detection and Fisherfaces will be used for recognition. This report also shows all the flows, functionality, requirements, and testing results of the application. |
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