http://www.colloquiam.com/wd/index.php?action=history&feed=atom&title=Ulker_2015a 2026-05-11T07:10:21Z Revision history for this page on the wiki MediaWiki 1.27.0-wmf.10 http://www.colloquiam.com/wd/index.php?title=Ulker_2015a&diff=190874&oldid=prev 2021-01-26T17:22:35Z

<p>Scipediacontent moved page <a href="/public/Draft_Content_111705702" class="mw-redirect" title="Draft Content 111705702">Draft Content 111705702</a> to <a href="/public/Ulker_2015a" title="Ulker 2015a">Ulker 2015a</a></p> <table class="diff diff-contentalign-left" data-mw="interface"> <tr style='vertical-align: top;' lang='en'> <td colspan='1' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='1' style="background-color: white; color:black; text-align: center;">Revision as of 17:22, 26 January 2021</td> </tr><tr><td colspan='2' style='text-align: center;' lang='en'><div class="mw-diff-empty">(No difference)</div> </td></tr></table>

Scipediacontent http://www.colloquiam.com/wd/index.php?title=Ulker_2015a&diff=190873&oldid=prev 2021-01-26T17:22:30Z

<p>Created page with &quot; == Abstract == Vision based intelligent transport system applications are extensively utilized and researched in recent years. Several applications with tracking, classific...&quot;</p> <p><b>New page</b></p><div><br /> == Abstract ==<br /> <br /> Vision based intelligent transport system applications are extensively utilized and researched in recent years. Several applications with tracking, classification and counting functionalities are used for automatization of traffic management. Work in this thesis aims to provide an accurate vehicle detection method for improving performance of these tasks. Vehicle detection starts with detection of moving objects, using a background subtraction algorithm. Then, accuracy of the foreground mask is improvedusingashadowdetectionalgorithm. Occlusionsaredetectedfrombothgeometrical properties of blobs in binary mask, and associations between objects from consecutive observations. A segmentation method based on the assumptions on objectgeometryunderocclusionisproposedandimplemented,todetectvehiclesunder occlusion correctly. Proposed solution is tested on several videos collected from different intersections. Results indicate a significant improvement in performance compared to the existing methods in literature. M.S. - Master of Science<br /> <br /> <br /> == Original document ==<br /> <br /> The different versions of the original document can be found in:<br /> <br /> * [https://hdl.handle.net/11511/24882 https://hdl.handle.net/11511/24882]</div>

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