Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Performance Analysis of a Surveillance System to Detect and Track Vehicles using Haar Cascaded Classifiers and Optical Flow method
University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
Rangamati Science & Technology University, Department of Computer Science & Engineering, Rangamati.
University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
Show others and affiliations
2017 (English)In: Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), New York: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 258-263Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the real time vehicle detection and tracking system, based on data, collected from a single camera. In this system, vehicles are detected by using Haar Feature-based Cascaded Classifier on static images, extracted from the video file. The advantage of this classifier is that, it uses floating numbers in computations and hence, 20% more accuracy can be achieved in comparison to other classifiers and features of classifiers such as LBP (Local Binary Pattern). Tracking of the vehicles is carried out using Lucas-Kanade and Horn Schunk Optical Flow method because it performs better than other methods such as Morphological and Correlation Transformations. The proposed system consists of vehicle detection and tracking; and it is evaluated by using real data, collected from the route networks of Chittagong City of Bangladesh.

Place, publisher, year, edition, pages
New York: Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 258-263
Series
IEEE Conference on Industrial Electronics and Applications, ISSN 2156-2318
National Category
Media and Communication Technology
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-68122DOI: 10.1109/ICIEA.2017.8282853ISI: 000426994400050Scopus ID: 2-s2.0-85047501241ISBN: 978-1-5090-6161-7 (electronic)OAI: oai:DiVA.org:ltu-68122DiVA, id: diva2:1194453
Conference
12th IEEE Conference on Industrial Electronics and Applications (ICIEA), Siem Reap, Cambodia, Jun 18-20, 2017
Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2018-06-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Andersson, Karl

Search in DiVA

By author/editor
Andersson, Karl
By organisation
Computer Science
Media and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 4 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf