Open Access   Article Go Back

Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper

Anshul Vishwakarma1 , Amit Khare2

Section:Review Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 721-724, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.721724

Online published on Jul 31, 2018

Copyright © Anshul Vishwakarma, Amit Khare . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Anshul Vishwakarma, Amit Khare, “Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.721-724, 2018.

MLA Style Citation: Anshul Vishwakarma, Amit Khare "Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper." International Journal of Computer Sciences and Engineering 6.7 (2018): 721-724.

APA Style Citation: Anshul Vishwakarma, Amit Khare, (2018). Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper. International Journal of Computer Sciences and Engineering, 6(7), 721-724.

BibTex Style Citation:
@article{Vishwakarma_2018,
author = {Anshul Vishwakarma, Amit Khare},
title = {Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {721-724},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2500},
doi = {https://doi.org/10.26438/ijcse/v6i7.721724}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.721724}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2500
TI - Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper
T2 - International Journal of Computer Sciences and Engineering
AU - Anshul Vishwakarma, Amit Khare
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 721-724
IS - 7
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
438 294 downloads 120 downloads
  
  
           

Abstract

Immediately Automatic video analysis from traffic surveillance cameras is a fast-emerging field based on computer vision techniques. It is a key technology to public safety, intelligent transport system (ITS) and for efficient management of traffic. An accurate and efficient tracking capability at the heart of such a system is essential for building higher level vision-based intelligence. Tracking is not a trivial task given the non-deterministic nature of the subjects, their motion, and the image capture process itself. The task of reliably detecting and tracking moving objects in surveillance video, which forms a basis for higher level intelligence applications, has many open questions. In this paper, we present an overview of the state of vehicle detection and tracking techniques and describes the different terminology to produce specification according need of current generation.

Key-Words / Index Term

Vehicle Detection, Video Surveillance, Object Recognition, Intelligent Traffic, Object Tracking

References

[1] Matthews, N. D., P. E. An, and C. J. Harris. "Vehicle detection and recognition for autonomous intelligent cruise control", Image. Speech and Intelligent Systems. 1995/ Research 6 Journal (1995).
[2] Suvarna Nandyal and Pushpalata Patil, “Vehicle Detection and Traffic Assessment Using Images”, International Journal of Computer Science and Mobile Computing, IJCSMC, Vol. 2, Issue. 9, September 2013, pp.8 – 17.
[3] Daniel Ponsa, Joan Serrat and Antonio M. Lo´pez, “On-board image-based vehicle detection and tracking”, Transactions of the Institute of Measurement and Control, Volume 33, Issue 7, 2011, pp. 783–805.
[4] Selvanayaki, K.S. and Rm. SomaSundaram, “Hybrid Approach for Detection and Recognition of Vehicles”, Journal of Computer Science, 2015, Volume 11, Issue 2, pp. 304-314.
[5] Raad Ahmed Hadi, Ghazali Sulong and Loay Edwar George, “Vehicle Detection and Tracking Techniques: A Concise Review”, Signal & Image Processing: An International Journal (SIPIJ) Volume 5, No.1, February 2014.
[6] Alper Yilmaz, Omar Javed, and Mubarak Shah. Object tracking: A survey. ACM Computing Surveys (CSUR), 38(4):13, 2006
[7] Bertozzi, Massimo, Alberto Broggi, Massimo Cellario, Alessandra Fascioli, Paolo Lombardi, and Marco Porta, "Artificial vision in road vehicles." Proceedings of the IEEE 90, no. 7 (2002): 1258-1271.
[8] N. Buch, S. A. Velastin, and J. Orwell, A review of computer vision techniques for the analysis of urban traffic. IEEE Transactions on Intelligent Transportation Systems, 12(3):920–939, 2011.
[9] Gupta, R. K. "Object detection and tracking in video image", PhD dissertation 2014.
[10] Ovseník, Ľuboš, Anna Kažimírová Kolesárová, and Ján Turán, "A System for Video Surveillance".
[11] Bojković, Zoran, Dragorad Milovanović, and Andreja Samčović, "Multimedia Communication Systems: Techniques, Standards, and Networks." (2002).
[12] Hannan, Mahammad Abdul, Chew Teik Gee, and Mohammad Saleh Javadi, "Automatic vehicle classification using fast neural network and classical neural network for traffic monitoring", Turkish Journal of Electrical Engineering & Computer Sciences 23, no. Sup. 1 (2015): 2031-2042.
[13] Khalid, Zebbara, Abdenbi Mazoul, and Mohamed El Ansari, "A new vehicle detection method." International Journal of Advanced Computer Science and Applications (IJACSA), Special Issue on Artificial Intelligence 2, no. 8 (2011).
[14] Psyllos, A., Christos-Nikolaos Anagnostopoulos, and Eleftherios Kayafas, "Vehicle model recognition from frontal view image measurements", Computer Standards & Interfaces 33, no. 2 (2011): 142-151.
[15] Kong, Qing-Jie, Lucidus Zhou, Gang Xiong, and Fenghua Zhu, "Automatic road detection for highway surveillance using frequency-domain information", In Service Operations and Logistics, and Informatics (SOLI), 2013 IEEE International Conference on, pp. 24-28, IEEE, 2013.
[16] Chen, Yiling, and GuoFeng Qin, "Video-Based Vehicle Detection And Classification In Challenging Scenarios", International Journal on Smart Sensing & Intelligent Systems 7, Number 3 (2014).
[17] Hargude, Sonali, and S. R. Idate. "i-surveillance: Intelligent surveillance system using background subtraction technique." In Computing Communication Control and automation (ICCUBEA), 2016 International Conference on, pp. 1-5. IEEE, 2016.
[18] Jitendra Oza , Zunnun Narmawala , Sudeep Tanwar, Pradeep Kr Singh ”Public Transport Tracking and its Issues”, International Journal of Computer Sciences and Engineering, Vol. 5, Issue 11, nov 2017