Implementing Real-time Visitor Counter Using Surveillance Video and MobileNet-SSD Object Detection: The Best Practice
Counters that keep track of the number of people who enter a building are a useful management tool for keeping everyone who uses it safe and happy. This paper aims to employ the MobileNet-SSD machine learning approach to implement a best practice for visitor counter. The researchers have to build a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad, College of Science for Women
2024-05-01
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| Series: | مجلة بغداد للعلوم |
| Subjects: | |
| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/10540 |
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| Summary: | Counters that keep track of the number of people who enter a building are a useful management tool for keeping everyone who uses it safe and happy. This paper aims to employ the MobileNet-SSD machine learning approach to implement a best practice for visitor counter. The researchers have to build a different scenario test dataset along with the MOT20 dataset to achieve the proposed methodology. Implementing different experiments in single-user, one-one; two-two users; many-two, and multiple users in different walking directions to detect and count shows varied results based on the experiment type. The best achieved by single-user and one-to-one model; both are scored 100% of detecting and calculating for in or out.
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| ISSN: | 2078-8665 2411-7986 |