@inproceedings{b91d386aee81458aa345dc74495d2c71,
title = "Robust Background Subtraction Based Person's Counting from Overhead View",
abstract = "In this paper, a computer vision based person counting system is presented which not only counts the number of persons in the scene but also keeps track on the number of persons entering and leaving the scene. The proposed system analyzes the video sequences which are captured by an overhead camera installed at about 7 meters height. Several background subtraction algorithms were compared and the best suited and efficient algorithm i.e Mixture of Gaussian (MoG) is selected for person counting from an overhead view. Whereas, a rectangular virtual zone, which covers all sides of the scene, is defined for counting the persons leaving and entering the scene. Moreover, in the proposed system a new real-life dataset is created using a single overhead camera. Ground truth is used for evaluation of the proposed system. The proposed algorithm achieves an accuracy of 98% for person counting and 95% for persons entering and leaving in the virtual zone. The overall average accuracy of the proposed system is 96%.",
keywords = "Background Subtraction, Overhead Camera, Person Counting, Person Detection",
author = "Misbah Ahmad and Imran Ahmed and Kaleem Ullah and Iqbal Khan and Awais Adnan",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018 ; Conference date: 08-11-2018 Through 10-11-2018",
year = "2018",
month = nov,
doi = "10.1109/UEMCON.2018.8796595",
language = "English",
series = "2018 9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "746--752",
editor = "Satyajit Chakrabarti and Saha, {Himadri Nath}",
booktitle = "2018 9th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2018",
address = "United States",
}