An efficient face recognition model using multiple angular images and deep neural network architecture
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
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| التنسيق: | أطروحة |
| اللغة: | English |
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Brac University
2024
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/10361/22124 |
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10361-22124 |
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10361-221242024-01-11T21:02:56Z An efficient face recognition model using multiple angular images and deep neural network architecture Subah, Silma Nath, Arpita Armisha, Mitheela das Binte Sakhawat, Sumaiya Alam Parbo, Md Nuhas Alam, Dr. Md. Ashraful Department of Computer Science and Engineering, Brac University Machine learning 3D model 2D model Multiple angle VGG16 ResNet50 Inception Net V3 HaarCascade Training Testing MTCNN. Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 37-39). Face surface information in three dimensions is one of the promising biometric modality that can improve the identification and increase the accuracy of verification of face recognition systems in challenging situations.This study proposed a system that recognizes faces from multiple angular images and deep neural networks.The proposed model can be divided into three steps: image acquisition, processing, and recognition.In acquisition part we take multiple angular images of the face which was taken by us and the angle was (0° to 180°)whereas right side was considered as pos itive(0° to +90°) and left side was considered as negative(0°to -90°). After that the images using Haar cascade and MTCNN algorithm segment the image, specially the face area.Then we used deep learning model VGG16,VGG19,InceptionNetV3 and ResNet50 to determine the face of person where the accuracy were 97%,92%,98%and 98% respectively.This article aggregates data from openly available multiple angle face databases to enable future research easier. The proposed system achieved more accuracy than the existing face recognition models when angle or motion is consid ered. That’s why we came up with an idea of various multiple angles which can detect a person in motion. The proposed system enables efficient face recognition in dynamic motion as well as with different angular deviations.It achieved higher accuracy than the existing 2D face recognition systems when the target object is in motion. Silma Subah Arpita Nath Mitheela das Armisha Sumaiya Binte Sakhawat Md Nuhas Alam Parbo B.Sc. in Computer Science and Engineering 2024-01-11T09:43:58Z 2024-01-11T09:43:58Z 2023 2023-01 Thesis ID: 18201088 ID: 18201089 ID: 18201101 ID: 18201076 ID: 17201020 http://hdl.handle.net/10361/22124 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 39 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Machine learning 3D model 2D model Multiple angle VGG16 ResNet50 Inception Net V3 HaarCascade Training Testing MTCNN. Neural networks (Computer science) |
| spellingShingle |
Machine learning 3D model 2D model Multiple angle VGG16 ResNet50 Inception Net V3 HaarCascade Training Testing MTCNN. Neural networks (Computer science) Subah, Silma Nath, Arpita Armisha, Mitheela das Binte Sakhawat, Sumaiya Alam Parbo, Md Nuhas An efficient face recognition model using multiple angular images and deep neural network architecture |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. |
| author2 |
Alam, Dr. Md. Ashraful |
| author_facet |
Alam, Dr. Md. Ashraful Subah, Silma Nath, Arpita Armisha, Mitheela das Binte Sakhawat, Sumaiya Alam Parbo, Md Nuhas |
| format |
Thesis |
| author |
Subah, Silma Nath, Arpita Armisha, Mitheela das Binte Sakhawat, Sumaiya Alam Parbo, Md Nuhas |
| author_sort |
Subah, Silma |
| title |
An efficient face recognition model using multiple angular images and deep neural network architecture |
| title_short |
An efficient face recognition model using multiple angular images and deep neural network architecture |
| title_full |
An efficient face recognition model using multiple angular images and deep neural network architecture |
| title_fullStr |
An efficient face recognition model using multiple angular images and deep neural network architecture |
| title_full_unstemmed |
An efficient face recognition model using multiple angular images and deep neural network architecture |
| title_sort |
efficient face recognition model using multiple angular images and deep neural network architecture |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22124 |
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