@inproceedings{4fc5e14b358e441a92e4463a7a4b1606,
title = "Tracking of multiple objects across multiple cameras with overlapping and non-overlapping views",
abstract = "In this paper, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping views in a unified framework without initial training. For single camera cases, Kalman filter and adaptive particle sampling are integrated for multiple objects tracking. When extended to multiple cameras cases, the relations between adjacent cameras are learned systematically by using image registration techniques for consistent handoff of tracking-object labels across cameras. In addition, object appearance measurement is employed to validate the labeling results. Experimental results demonstrate the performance of our approach on real video sequences for cameras with overlapping and non-overlapping views.",
author = "Zhu, {Liang Jia} and Hwang, {Jenq Neng} and Cheng, {Hsu Yung}",
year = "2009",
doi = "10.1109/ISCAS.2009.5117941",
language = "???core.languages.en_GB???",
isbn = "9781424438280",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
pages = "1056--1060",
booktitle = "2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009",
note = "null ; Conference date: 24-05-2009 Through 27-05-2009",
}