Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Idioma: | English |
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Brac University
2022
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| Acesso em linha: | http://hdl.handle.net/10361/17345 |
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10361-173452022-09-27T21:02:18Z Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision Datta, Anurag Fatema, Kaniz Tasnim, Nowshin Sitara, Faria Das, Mrithik Kanti Chakrabarty, Amitabha Department of Computer Science and Engineering, Brac University Human detection Social distancing YOLO algorithm Image processing Deep learning TensorFlow Computer vision MobileNet SSD Image processing -- Digital techniques. Cognitive learning theory (Deep learning) Machine learning Human-machine systems This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 46-51). The COVID-19 pandemic has significantly affected day to day lifestyle all over the planet by disequilibrating social order. It moreover added anxiety about the capability of the world’s democracies to cope with the vital and crucial emergencies. We should urgently restore a necessary methodology to fathom the emergency and rigorously depict a course forward. The Division of Public Health authorities have recommended everyone to uphold social distancing with a view to diminishing the number of physical encounters. To keep a record of social distancing from an overhead standpoint, we established a computer vision deep learning framework. Our schemed system utilized the object recognition paradigm to spot and identify people in video sequences or frames. In our research, we assess the classification performance of two distinct multilayer neural network models named YOLO using OpenCV and TensorFlow which are used in the implementation process of an automatic recognition system. Amongst these using SSD, CUDA, and CUDNN we achieved a success rate in the classification. Neural networks were trained on a dataset where we used COCO dataset methods. At a time when neural networks are increasingly being utilized for a spectrum of uses, it is essential to select the proper model for the classification process that can attain the ultimate accuracy with the least amount of training duration. The demonstration created by us allows the insertion of images and the creation of their datasets, this allows the user to train a model using their chosen parameters. The models can then be saved and used in other systems. Moreover, to prevent future crucial situations and by keeping in the head about COVID affected situations on various global aspects this work will become an integral part of contributing to the term “Social Distancing” by implementing this sustainably and with one of the best results outcomes in our proposed image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision. Because coronavirus sickness has had such a negative influence on the world economy, this research tries to reduce the further impacts while minimizing resource loss. Also, create a very accurate detection mechanism to aid in the tracking of social distancing. In these types of serious situations, adequate actions must be taken and help to assist further research and work as an example for future works on this segment. Anurag Datta Kaniz Fatema Nowshin Tasnim Faria Sitara Mrithik Kanti Das B. Computer Science and Engineering 2022-09-27T06:11:29Z 2022-09-27T06:11:29Z 2022 2022-05 Thesis ID 18101369 ID 19201132 ID 19101655 ID 18101295 ID 17101047 http://hdl.handle.net/10361/17345 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. 51 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Human detection Social distancing YOLO algorithm Image processing Deep learning TensorFlow Computer vision MobileNet SSD Image processing -- Digital techniques. Cognitive learning theory (Deep learning) Machine learning Human-machine systems |
| spellingShingle |
Human detection Social distancing YOLO algorithm Image processing Deep learning TensorFlow Computer vision MobileNet SSD Image processing -- Digital techniques. Cognitive learning theory (Deep learning) Machine learning Human-machine systems Datta, Anurag Fatema, Kaniz Tasnim, Nowshin Sitara, Faria Das, Mrithik Kanti Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Datta, Anurag Fatema, Kaniz Tasnim, Nowshin Sitara, Faria Das, Mrithik Kanti |
| format |
Thesis |
| author |
Datta, Anurag Fatema, Kaniz Tasnim, Nowshin Sitara, Faria Das, Mrithik Kanti |
| author_sort |
Datta, Anurag |
| title |
Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| title_short |
Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| title_full |
Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| title_fullStr |
Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| title_full_unstemmed |
Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| title_sort |
image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/17345 |
| work_keys_str_mv |
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