@inproceedings{c546532f81b541319962e1d3636dd142,
title = "A novel approach for people counting and tracking from crowd video",
abstract = "Crowd analysis on video recordings is an important research area currently. In this work, a combined crowd density estimation method is presented to overcome this problem. To improve the accuracy of the system two different estimators run simultaneously and a blob is marked as a person only if both estimators mark it as person. One of the main problems in crowd density estimation is occlusion. To overcome this problem we tracked the trajectories of blobs by using a Kalman filter. The method was applied to three common benchmark data which are PETS2009, UCSD and Grand Central. The results confirm the proposed method's success.",
keywords = "Crowd density, Kalman filtering, Optical flow, SIFT, Video processing, complex wavelet transform",
author = "Sagun, {M. Ayyuce Kizrak} and Bulent Bolat",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2017 ; Conference date: 03-07-2017 Through 05-07-2017",
year = "2017",
month = aug,
day = "3",
doi = "10.1109/INISTA.2017.8001170",
language = "English",
series = "Proceedings - 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "277--281",
editor = "Tulay Yildirim and Ireneusz Czarnowski and Piotr Jedrzejowicz",
booktitle = "Proceedings - 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2017",
}