Automated Gait Trait Analysis and Applications

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dc.contributor.advisorYanushkevich, Svetlana N.
dc.contributor.authorKozlow, Patrick
dc.contributor.committeememberBartley, Norman R.
dc.contributor.committeememberGoldsmith, Peter B.
dc.date2018-11
dc.date.accessioned2018-10-01T16:32:29Z
dc.date.available2018-10-01T16:32:29Z
dc.date.issued2018-09-20
dc.description.abstractThe main focus of this thesis is the development and feasibility testing of a proposed gait biometric screening system based on the Kinect v2 sensor. To achieve contactless gait biometric extraction the system uses a virtual Kinect 3D skeleton to construct models in real time. These models are then used to identify an individual's gait characteristics. The features found from the virtual models are passed through a gait recognition system which provides insight into what type of gait pattern is being observed by the camera. Extensive experiments with different classification methods such as Support Vector Machines, K-Nearest-Neighbors, and Dynamic Bayesian Networks are tested to determine the effectiveness of the system. The proposed gait recognition network is tested using locally collected and publically available databases to validate the results and prove that the system is feasible.en_US
dc.identifier.citationKozlow, P. (2018). Automated Gait Trait Analysis and Applications (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/33062en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/33062
dc.identifier.urihttp://hdl.handle.net/1880/108709
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.facultySchulich School of Engineering
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectGait
dc.subjectKinect
dc.subjectDynamic Bayesian network
dc.subjectBiometrics
dc.subjectHuman Identification
dc.subject.classificationArtificial Intelligenceen_US
dc.subject.classificationEngineering--Biomedicalen_US
dc.subject.classificationEngineering--Electronics and Electricalen_US
dc.titleAutomated Gait Trait Analysis and Applications
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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