Frame based object detection - an application for traffic monitoring

In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow r...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chin Hong Low, Ming Kiat Lee, Siak Wang Khor
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page V3-12
container_issue
container_start_page V3-9
container_title
container_volume 3
creator Chin Hong Low
Ming Kiat Lee
Siak Wang Khor
description In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow removal method is applied in the preprocessing phase of the system to amplify the accuracy of detection. MATLAB is the major platform for developing this system. By differentiating the background and foreground of the video scenes using MATLAB embedded functions, the foreground regions are segmented as the objects. The segmented objects are saved for further development of computer vision applications such as object recognition and classification. The proposed system is tested with four traffic video scenes and the experimental results show that the system works well with an accuracy of approximately 90% achieved.
doi_str_mv 10.1109/ICCET.2010.5485742
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5485742</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5485742</ieee_id><sourcerecordid>5485742</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-33bc6d91c7d780110f5fa5e69c4254803b951c72ac4e5821a1c9cb0a4b4d12903</originalsourceid><addsrcrecordid>eNo1T81OwzAYC0KTgNEXgEteoCM_X5rmiMo2Jk3i0vv0JU2mTOuP0l54eyIYvli2Jcsm5IWzDefMvB2aZttuBMtaQa00iDvyxEEAVBIMvyeF0fW_1vKBFPN8YRmgRKX5I_nYJew9tTj7jo724t1CO79kiuNAS4oDxWm6Roe_RhgTXRKGEB3txyEuY4rD-ZmsAl5nX9x4Tdrdtm0-y-PX_tC8H8to2FJKaV3VGe50p2uW5wcVUPnKOBB5PJPWqBwKdOBVLThyZ5xlCBY6LgyTa_L6Vxu996cpxR7T9-n2W_4AvBNLHA</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Frame based object detection - an application for traffic monitoring</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Chin Hong Low ; Ming Kiat Lee ; Siak Wang Khor</creator><creatorcontrib>Chin Hong Low ; Ming Kiat Lee ; Siak Wang Khor</creatorcontrib><description>In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow removal method is applied in the preprocessing phase of the system to amplify the accuracy of detection. MATLAB is the major platform for developing this system. By differentiating the background and foreground of the video scenes using MATLAB embedded functions, the foreground regions are segmented as the objects. The segmented objects are saved for further development of computer vision applications such as object recognition and classification. The proposed system is tested with four traffic video scenes and the experimental results show that the system works well with an accuracy of approximately 90% achieved.</description><identifier>ISBN: 9781424463473</identifier><identifier>ISBN: 1424463475</identifier><identifier>EISBN: 1424463491</identifier><identifier>EISBN: 1424463483</identifier><identifier>EISBN: 9781424463480</identifier><identifier>EISBN: 9781424463497</identifier><identifier>DOI: 10.1109/ICCET.2010.5485742</identifier><language>eng</language><publisher>IEEE</publisher><subject>Application software ; background subtraction ; Computer vision ; Face detection ; Layout ; MATLAB ; Monitoring ; Object detection ; Object recognition ; object segmentation ; Phase detection ; shadow removal ; Surveillance ; traffic flow monitoring</subject><ispartof>2010 2nd International Conference on Computer Engineering and Technology, 2010, Vol.3, p.V3-9-V3-12</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5485742$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5485742$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chin Hong Low</creatorcontrib><creatorcontrib>Ming Kiat Lee</creatorcontrib><creatorcontrib>Siak Wang Khor</creatorcontrib><title>Frame based object detection - an application for traffic monitoring</title><title>2010 2nd International Conference on Computer Engineering and Technology</title><addtitle>ICCET</addtitle><description>In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow removal method is applied in the preprocessing phase of the system to amplify the accuracy of detection. MATLAB is the major platform for developing this system. By differentiating the background and foreground of the video scenes using MATLAB embedded functions, the foreground regions are segmented as the objects. The segmented objects are saved for further development of computer vision applications such as object recognition and classification. The proposed system is tested with four traffic video scenes and the experimental results show that the system works well with an accuracy of approximately 90% achieved.</description><subject>Application software</subject><subject>background subtraction</subject><subject>Computer vision</subject><subject>Face detection</subject><subject>Layout</subject><subject>MATLAB</subject><subject>Monitoring</subject><subject>Object detection</subject><subject>Object recognition</subject><subject>object segmentation</subject><subject>Phase detection</subject><subject>shadow removal</subject><subject>Surveillance</subject><subject>traffic flow monitoring</subject><isbn>9781424463473</isbn><isbn>1424463475</isbn><isbn>1424463491</isbn><isbn>1424463483</isbn><isbn>9781424463480</isbn><isbn>9781424463497</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1T81OwzAYC0KTgNEXgEteoCM_X5rmiMo2Jk3i0vv0JU2mTOuP0l54eyIYvli2Jcsm5IWzDefMvB2aZttuBMtaQa00iDvyxEEAVBIMvyeF0fW_1vKBFPN8YRmgRKX5I_nYJew9tTj7jo724t1CO79kiuNAS4oDxWm6Roe_RhgTXRKGEB3txyEuY4rD-ZmsAl5nX9x4Tdrdtm0-y-PX_tC8H8to2FJKaV3VGe50p2uW5wcVUPnKOBB5PJPWqBwKdOBVLThyZ5xlCBY6LgyTa_L6Vxu996cpxR7T9-n2W_4AvBNLHA</recordid><startdate>201004</startdate><enddate>201004</enddate><creator>Chin Hong Low</creator><creator>Ming Kiat Lee</creator><creator>Siak Wang Khor</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201004</creationdate><title>Frame based object detection - an application for traffic monitoring</title><author>Chin Hong Low ; Ming Kiat Lee ; Siak Wang Khor</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-33bc6d91c7d780110f5fa5e69c4254803b951c72ac4e5821a1c9cb0a4b4d12903</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Application software</topic><topic>background subtraction</topic><topic>Computer vision</topic><topic>Face detection</topic><topic>Layout</topic><topic>MATLAB</topic><topic>Monitoring</topic><topic>Object detection</topic><topic>Object recognition</topic><topic>object segmentation</topic><topic>Phase detection</topic><topic>shadow removal</topic><topic>Surveillance</topic><topic>traffic flow monitoring</topic><toplevel>online_resources</toplevel><creatorcontrib>Chin Hong Low</creatorcontrib><creatorcontrib>Ming Kiat Lee</creatorcontrib><creatorcontrib>Siak Wang Khor</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chin Hong Low</au><au>Ming Kiat Lee</au><au>Siak Wang Khor</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Frame based object detection - an application for traffic monitoring</atitle><btitle>2010 2nd International Conference on Computer Engineering and Technology</btitle><stitle>ICCET</stitle><date>2010-04</date><risdate>2010</risdate><volume>3</volume><spage>V3-9</spage><epage>V3-12</epage><pages>V3-9-V3-12</pages><isbn>9781424463473</isbn><isbn>1424463475</isbn><eisbn>1424463491</eisbn><eisbn>1424463483</eisbn><eisbn>9781424463480</eisbn><eisbn>9781424463497</eisbn><abstract>In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow removal method is applied in the preprocessing phase of the system to amplify the accuracy of detection. MATLAB is the major platform for developing this system. By differentiating the background and foreground of the video scenes using MATLAB embedded functions, the foreground regions are segmented as the objects. The segmented objects are saved for further development of computer vision applications such as object recognition and classification. The proposed system is tested with four traffic video scenes and the experimental results show that the system works well with an accuracy of approximately 90% achieved.</abstract><pub>IEEE</pub><doi>10.1109/ICCET.2010.5485742</doi></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9781424463473
ispartof 2010 2nd International Conference on Computer Engineering and Technology, 2010, Vol.3, p.V3-9-V3-12
issn
language eng
recordid cdi_ieee_primary_5485742
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Application software
background subtraction
Computer vision
Face detection
Layout
MATLAB
Monitoring
Object detection
Object recognition
object segmentation
Phase detection
shadow removal
Surveillance
traffic flow monitoring
title Frame based object detection - an application for traffic monitoring
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T16%3A22%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Frame%20based%20object%20detection%20-%20an%20application%20for%20traffic%20monitoring&rft.btitle=2010%202nd%20International%20Conference%20on%20Computer%20Engineering%20and%20Technology&rft.au=Chin%20Hong%20Low&rft.date=2010-04&rft.volume=3&rft.spage=V3-9&rft.epage=V3-12&rft.pages=V3-9-V3-12&rft.isbn=9781424463473&rft.isbn_list=1424463475&rft_id=info:doi/10.1109/ICCET.2010.5485742&rft_dat=%3Cieee_6IE%3E5485742%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424463491&rft.eisbn_list=1424463483&rft.eisbn_list=9781424463480&rft.eisbn_list=9781424463497&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5485742&rfr_iscdi=true