Implementing Real-time Visitor Counter Using Surveillance Video and MobileNet-SSD Object Detection: The Best Practice

Main Article Content

Nasser Al Musalhi
https://orcid.org/0000-0003-4839-1058
Ali Mohammed Al Wahaibi
Mohammed Abbas

Abstract

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.

Article Details

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1.
Implementing Real-time Visitor Counter Using Surveillance Video and MobileNet-SSD Object Detection: The Best Practice. Baghdad Sci.J [Internet]. 2024 May 25 [cited 2024 Jun. 17];21(5(SI):1775. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/10540
Section
Special Issue - (ICCDA) International Conference on Computing and Data Analytics

How to Cite

1.
Implementing Real-time Visitor Counter Using Surveillance Video and MobileNet-SSD Object Detection: The Best Practice. Baghdad Sci.J [Internet]. 2024 May 25 [cited 2024 Jun. 17];21(5(SI):1775. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/10540

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