A computer vision based approach for stalking detection using CNN-LSTM hybrid model
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
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| פורמט: | Thesis |
| שפה: | English |
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Brac University
2023
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| גישה מקוונת: | http://hdl.handle.net/10361/18248 |
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10361-182482023-05-09T21:01:54Z A computer vision based approach for stalking detection using CNN-LSTM hybrid model Iqbal, Shahriar Hasan, Murad Faisal, Md Billal Hossain Neloy, Md.Musnad Hossin Kabir, Md. Tonmoy Alam, Md. Golam Rabiul Reza, Md. Tanzim Department of Computer Science and Engineering, Brac University Stalking Non-stalking Prediction LSTM CNN Neural networks Classification Machine learning Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 31-34). The next level of revolution toward a better world could involve combining human security with machine intelligence. In recent years, stalking in public areas has become a pervasive issue, and women are disproportionately affected. In order to solve the problem, we want to design a model that can identify public-space stalking. There have been several study papers and publications written on the topic of stalking. However, most of them relied on spatial co-occurrence for the detection of suspicious actions and face recognition, which does not adequately address the problem. Using a hybrid mix of CNN and LSTM, we explain in our study a model for determining the presence of a stalker situation utilizing a dataset of video footage. The proposed model was evaluated using two approaches: one using manual feature extraction and the other using dynamic feature extraction. The manual feature extraction approach was evaluated with three distinct machine learning classifiers (SVM,KNN, and Random Forest), whereas the dynamic feature extraction method was examined with two different CNN models (VGG16 and ResNet50) and a CNNLSTM hybrid model. The CNN-LSTM hybrid model has the highest accuracy of any of these models, at 89%. Experiment results indicate that the CNN-LSTM hybrid model detects a stalking scenario with a spatio-temporal advantage and provides a better classification result than other models. Shahriar Iqbal Murad Hasan Md Billal Hossain Faisal Md.Musnad Hossin Neloy Md. Tonmoy Kabir B. Computer Science 2023-05-09T04:16:55Z 2023-05-09T04:16:55Z 2022 2022-05 Thesis ID 18101643 ID 18301253 ID 18301066 ID 22141032 ID 18301245 http://hdl.handle.net/10361/18248 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. 34 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Stalking Non-stalking Prediction LSTM CNN Neural networks Classification Machine learning Neural networks (Computer science) |
| spellingShingle |
Stalking Non-stalking Prediction LSTM CNN Neural networks Classification Machine learning Neural networks (Computer science) Iqbal, Shahriar Hasan, Murad Faisal, Md Billal Hossain Neloy, Md.Musnad Hossin Kabir, Md. Tonmoy A computer vision based approach for stalking detection using CNN-LSTM hybrid model |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. |
| author2 |
Alam, Md. Golam Rabiul |
| author_facet |
Alam, Md. Golam Rabiul Iqbal, Shahriar Hasan, Murad Faisal, Md Billal Hossain Neloy, Md.Musnad Hossin Kabir, Md. Tonmoy |
| format |
Thesis |
| author |
Iqbal, Shahriar Hasan, Murad Faisal, Md Billal Hossain Neloy, Md.Musnad Hossin Kabir, Md. Tonmoy |
| author_sort |
Iqbal, Shahriar |
| title |
A computer vision based approach for stalking detection using CNN-LSTM hybrid model |
| title_short |
A computer vision based approach for stalking detection using CNN-LSTM hybrid model |
| title_full |
A computer vision based approach for stalking detection using CNN-LSTM hybrid model |
| title_fullStr |
A computer vision based approach for stalking detection using CNN-LSTM hybrid model |
| title_full_unstemmed |
A computer vision based approach for stalking detection using CNN-LSTM hybrid model |
| title_sort |
computer vision based approach for stalking detection using cnn-lstm hybrid model |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/18248 |
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