Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Real time fuzzy based traffic flow estimation and analysis. / Abbas, Muhammad; Mehboob, Fozia; Khan, Shoab A.; Rauf, Abdul; Jiang, Richard.
New Knowledge in Information Systems and Technologies - Volume 2. ed. / Álvaro Rocha; Sandra Costanzo; Hojjat Adeli; Luís Paulo Reis. Vol. 2 Springer-Verlag, 2019. p. 472-482 (Advances in Intelligent Systems and Computing; Vol. 931).Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Real time fuzzy based traffic flow estimation and analysis
AU - Abbas, Muhammad
AU - Mehboob, Fozia
AU - Khan, Shoab A.
AU - Rauf, Abdul
AU - Jiang, Richard
PY - 2019/4/19
Y1 - 2019/4/19
N2 - Real-time traffic flow analysis using road mounted surveillance cameras presents multitude of benefits. In this paper, we used surveillance videos to design optical flow based technique for robust motion analysis and estimation. Region growing method is employed for detection of objects of interest. Autonomous density estimation of vehicles is crucial for traffic congestion analysis so that countermeasures can be taken at the earliest possible opportunity. A video based data extraction scheme for traffic data is proposed to determine the right traffic conditions which alleviates the false alarms and detrimental noise effects. Evaluation of proposed system is done by applying approach on several surveillance videos obtained from different sources and scenarios. An experimental study illustrates estimation and analysis results accuracy as compared to state-of-the-art approaches.
AB - Real-time traffic flow analysis using road mounted surveillance cameras presents multitude of benefits. In this paper, we used surveillance videos to design optical flow based technique for robust motion analysis and estimation. Region growing method is employed for detection of objects of interest. Autonomous density estimation of vehicles is crucial for traffic congestion analysis so that countermeasures can be taken at the earliest possible opportunity. A video based data extraction scheme for traffic data is proposed to determine the right traffic conditions which alleviates the false alarms and detrimental noise effects. Evaluation of proposed system is done by applying approach on several surveillance videos obtained from different sources and scenarios. An experimental study illustrates estimation and analysis results accuracy as compared to state-of-the-art approaches.
KW - Flow estimation
KW - Smart city
KW - Traffic surveillance videos
U2 - 10.1007/978-3-030-16184-2_45
DO - 10.1007/978-3-030-16184-2_45
M3 - Conference contribution/Paper
AN - SCOPUS:85065078869
SN - 9783030161835
VL - 2
T3 - Advances in Intelligent Systems and Computing
SP - 472
EP - 482
BT - New Knowledge in Information Systems and Technologies - Volume 2
A2 - Rocha, Álvaro
A2 - Costanzo, Sandra
A2 - Adeli, Hojjat
A2 - Reis, Luís Paulo
PB - Springer-Verlag
T2 - World Conference on Information Systems and Technologies, WorldCIST 2019
Y2 - 16 April 2019 through 19 April 2019
ER -