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JCR Impact Factor: 1.102
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Issues per year: 4
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Next issue: May 2021
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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

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  2/2010 - 5

 HIGH-IMPACT PAPER 

Kalman Filter Based Tracking in an Video Surveillance System

SULIMAN, C. See more information about SULIMAN, C. on SCOPUS See more information about SULIMAN, C. on IEEExplore See more information about SULIMAN, C. on Web of Science, CRUCERU, C. See more information about  CRUCERU, C. on SCOPUS See more information about  CRUCERU, C. on SCOPUS See more information about CRUCERU, C. on Web of Science, MOLDOVEANU, F. See more information about MOLDOVEANU, F. on SCOPUS See more information about MOLDOVEANU, F. on SCOPUS See more information about MOLDOVEANU, F. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (2,017 KB) | Citation | Downloads: 1,680 | Views: 6,596

Author keywords
video surveillance system, optical flow, Kalman filtering, image processing, tracking

References keywords
tracking(11), surveillance(8), video(6), intern(5), human(5), processing(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-05-31
Volume 10, Issue 2, Year 2010, On page(s): 30 - 34
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.02005
Web of Science Accession Number: 000280312600005
SCOPUS ID: 77954639594

Abstract
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In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 9 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 12
View record in SCOPUS®
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Cited-By CrossRef

[1] Alternating Projections Filtering Algorithm to Track Moving Objects, Qranfal, Youssef, Journal of Applied Mathematics, ISSN 1110-757X, Issue , 2019.
Digital Object Identifier: 10.1155/2019/8450905
[CrossRef]

[2] A Novel Target Tracking Algorithm for Simultaneous Measurements of Radar and Infrared Sensors, GHAZAL, M., DOUSTMOHAMMADI, A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 16, 2016.
Digital Object Identifier: 10.4316/AECE.2016.03009
[CrossRef] [Full text]

[3] Incremental multi-class semi-supervised clustering regularized by Kalman filtering, Mehrkanoon, Siamak, Agudelo, Oscar Mauricio, Suykens, Johan A.K., Neural Networks, ISSN 0893-6080, Issue , 2015.
Digital Object Identifier: 10.1016/j.neunet.2015.08.001
[CrossRef]

[4] 6DOF Wireless Tracking Wand Using MARG and Vision Sensor Fusion, Chintalapalli, Harinadha Reddy, Patil, Shashidhar, Nam, Sanghun, Park, Sungsoo, Chai, Young Ho, International Journal of Distributed Sensor Networks, ISSN 1550-1477, Issue 6, Volume 10, 2014.
Digital Object Identifier: 10.1155/2014/864768
[CrossRef]

[5] Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND, RISTIC-DURRANT, D., GRIGORESCU, S. M., GRASER, A., COJBASIC, Z., NIKOLIC, V., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 11, 2011.
Digital Object Identifier: 10.4316/AECE.2011.04003
[CrossRef] [Full text]

[6] Orthogonal Functions Applied in Antenna Positioning, NIKOLI, S., ANTIC, D., DANKOVIC, B., MILOJKOVIC, M., JOVANOVIC, Z., PERIC, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 10, 2010.
Digital Object Identifier: 10.4316/aece.2010.04006
[CrossRef] [Full text]

[7] Video-based face recognition by Auto-Associative Elman Neural network, Zhang, Bailing, Zhou, Juntao, 2014 7th International Congress on Image and Signal Processing, ISBN 978-1-4799-5835-1, 2014.
Digital Object Identifier: 10.1109/CISP.2014.7003755
[CrossRef]

[8] Raspberry pi based single object tracking using Bayesian filter example, DipaliAmbadas, Bhor, Bodake, Shekhar H., 2017 2nd International Conference for Convergence in Technology (I2CT), ISBN 978-1-5090-4307-1, 2017.
Digital Object Identifier: 10.1109/I2CT.2017.8226153
[CrossRef]

[9] Background modelling, detection and tracking of human in video surveillance system, Kaur, Rajvir, Singh, Sonit, 2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), ISBN 978-1-4799-5871-9, 2014.
Digital Object Identifier: 10.1109/CIPECH.2014.7019097
[CrossRef]

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