2D face recognition
We know Face Recognition technology is widely used in our society today. Instances of this would be the in security, for example, unlocking of phones with face recognition. Also, in surveillance technology for detecting wanted criminals in the airport. Recognising faces is a skill that we as human b...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/139064 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | We know Face Recognition technology is widely used in our society today. Instances of this would be the in security, for example, unlocking of phones with face recognition. Also, in surveillance technology for detecting wanted criminals in the airport. Recognising faces is a skill that we as human beings exercise daily without much thought, whether it be to identify friends or family, or to recognise famous faces on the streets that we know from the internet or television. How are we able to allow a computer to acquire such a skill? This project will evaluate the effectiveness of the Local Binary Patterns Histogram feature extraction technique in face recognition. This project will conduct tests using the Labelled Faces in the Wild dataset, using Haar Cascade for face detection, followed by Local Binary Pattern Histogram for feature extraction to extract data for training a Linear Support Vector Classifier model. This model will then be tested with faces from the Labelled Faces in the Wild dataset and also be carried out with live subjects to simulate real-world conditions, under different illuminations and poses. |
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