Real time dynamic facial recognition of subject at motion using angular image
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
| Príomhchruthaitheoirí: | , , , |
|---|---|
| Rannpháirtithe: | |
| Formáid: | Tráchtas |
| Teanga: | English |
| Foilsithe / Cruthaithe: |
Brac University
2024
|
| Ábhair: | |
| Rochtain ar líne: | http://hdl.handle.net/10361/22848 |
| id |
10361-22848 |
|---|---|
| record_format |
dspace |
| spelling |
10361-228482024-05-16T21:03:59Z Real time dynamic facial recognition of subject at motion using angular image Tasneem, Sharah Rahman, Ramisa Yashfi Mansur, Ayman Nowshad, MD. Meherab Hossain Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University Facial recognition Angular deviation TensorRT Deep learning Angular image Pattern recognition Image processing This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 42-44). In the developing world keeping track of violations or implementing a secured environment has become crucial. In order to address such issues dynamic facial recognition could be developed in such a way that it can facilitate and address all these issues. Dynamic facial recognition is a real time recognition of a subject while it is in motion. Different well known pre-trained models for facial recognition such as ResNet50, VGG19, VGG16, DenseNet169, Inceptionv3 and MobileNetv2 were customized according to the requirement of the dataset to bring about the highest accuracy. Before training the models, the process composed of several steps involving data acquisition which retrieved pictures from various angles of subject. To detect faces and create bounding boxes around the faces as well as marking facial landmarks such as eyes, nose and mouth MTCNN algorithm has been used. In order to compare, the test dataset was divided into two different types where one consisted of all the data and the other consisted of only the images with 120 degree deviation. This helped us to understand how feature extraction is an important factor for facial recognition as all the trained models provided improved and better results with the filtered dataset. Among all the models trained, it can be concluded that the best performing model for our custom dataset is VGG19. Sharah Tasneem Ramisa Yashfi Rahman Ayman Mansur MD. Meherab Hossain Nowshad B.Sc in Computer Science 2024-05-16T04:49:36Z 2024-05-16T04:49:36Z ©2024 2024-01 Thesis ID: 20101186 ID: 20101157 ID: 20101432 ID: 20301308 http://hdl.handle.net/10361/22848 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. 49 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Facial recognition Angular deviation TensorRT Deep learning Angular image Pattern recognition Image processing |
| spellingShingle |
Facial recognition Angular deviation TensorRT Deep learning Angular image Pattern recognition Image processing Tasneem, Sharah Rahman, Ramisa Yashfi Mansur, Ayman Nowshad, MD. Meherab Hossain Real time dynamic facial recognition of subject at motion using angular image |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. |
| author2 |
Alam, Md. Ashraful |
| author_facet |
Alam, Md. Ashraful Tasneem, Sharah Rahman, Ramisa Yashfi Mansur, Ayman Nowshad, MD. Meherab Hossain |
| format |
Thesis |
| author |
Tasneem, Sharah Rahman, Ramisa Yashfi Mansur, Ayman Nowshad, MD. Meherab Hossain |
| author_sort |
Tasneem, Sharah |
| title |
Real time dynamic facial recognition of subject at motion using angular image |
| title_short |
Real time dynamic facial recognition of subject at motion using angular image |
| title_full |
Real time dynamic facial recognition of subject at motion using angular image |
| title_fullStr |
Real time dynamic facial recognition of subject at motion using angular image |
| title_full_unstemmed |
Real time dynamic facial recognition of subject at motion using angular image |
| title_sort |
real time dynamic facial recognition of subject at motion using angular image |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22848 |
| work_keys_str_mv |
AT tasneemsharah realtimedynamicfacialrecognitionofsubjectatmotionusingangularimage AT rahmanramisayashfi realtimedynamicfacialrecognitionofsubjectatmotionusingangularimage AT mansurayman realtimedynamicfacialrecognitionofsubjectatmotionusingangularimage AT nowshadmdmeherabhossain realtimedynamicfacialrecognitionofsubjectatmotionusingangularimage |
| _version_ |
1814309314202959872 |