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dc.contributor.authorNguyen, Chuong Hoangen_US
dc.date.accessioned2014-03-14T20:38:18Z
dc.date.available2014-03-14T20:38:18Z
dc.date.issued2013-04-30en_US
dc.identifier.otheretd-05222013-102925en_US
dc.identifier.urihttp://hdl.handle.net/10919/33127
dc.description.abstractThis thesis attempts to develop features identification and tracking system for an autonomous ground vehicle by focusing on four fundamental tasks: Motion detection, object tracking, scene recognition, and object detection and recognition. For motion detection, we combined the background subtraction method using the mixture of Gaussian models and the optical flow to highlight any moving objects or new entering objects which stayed still. To increase robustness for object tracking result, we used the Kalman filter to combine the tracking method based on the color histogram and the method based on invariant features. For scene recognition, we applied the algorithm Census Transform Histogram (CENTRIST), which is based on Census Transform images of the training data and the Support Vector Machine classifier, to recognize a total of 8 scene categories. Because detecting the horizon is also an important task for many navigation applications, we also performed horizon detection in this thesis. Finally, the deformable parts-based models algorithm was implemented to detect some common objects, such as humans and vehicles. Furthermore, objects were only detected in the area under the horizon to reduce the detecting time and false matching rate.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartNguyen_CH_T_2013_permissions.pdfen_US
dc.relation.haspartNguyen_CH_T_2013.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectMotion detectionen_US
dc.subjectobject trackingen_US
dc.subjectscene recognitionen_US
dc.subjectobject detectionen_US
dc.titleFeatures identification and tracking for an autonomous ground vehicleen_US
dc.typeThesisen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairWicks, Alfred L.en_US
dc.contributor.committeememberAbbott, A. Lynnen_US
dc.contributor.committeememberLeonessa, Alexanderen_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05222013-102925/en_US
dc.date.sdate2013-05-22en_US
dc.date.rdate2013-06-14
dc.date.adate2013-06-14en_US


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