Model-Based Gait and Action Recognition Using Kinect

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atmire.migration.oldid4622
dc.contributor.advisorGavrilova, Marina
dc.contributor.authorAhmed, Faisal
dc.contributor.committeememberGavrilova, Marina
dc.contributor.committeememberAlim, Usman
dc.contributor.committeememberMintchev, Martin
dc.date.accessioned2016-07-12T21:26:40Z
dc.date.available2016-07-12T21:26:40Z
dc.date.issued2016
dc.date.submitted2016en
dc.description.abstractBeing the very first in the category of low-cost consumer-level depth sensors, the recent release of Microsoft Kinect has opened the door to a new generation of computer vision and biometric security applications. This thesis focuses on designing new methodologies for Kinect-based gait and action recognition systems that utilize the Kinect 3D virtual skeleton to construct effective and robust motion representations. The proposed gait recognition method focuses on designing a feature descriptor that can capture person-specific distinct motion patterns, caused by the influence of human physiology and behavioral traits. On the other hand, the proposed action recognition method involves constructing a person-independent feature descriptor that can suppress person-specific motion traits while highlighting a more generic and high level description of action-specific skeletal joint movements. Extensive experiments with three recently released public benchmark databases demonstrate the effectiveness of the proposed methodologies, compared against state-of-the-art gait and action recognition methods.en_US
dc.identifier.citationAhmed, F. (2016). Model-Based Gait and Action Recognition Using Kinect (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26931en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/26931
dc.identifier.urihttp://hdl.handle.net/11023/3122
dc.language.isoeng
dc.publisher.facultyGraduate Studies
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.subjectComputer Science
dc.subject.classificationBiometric Gait Recognitionen_US
dc.subject.classificationAction Recognitionen_US
dc.subject.classificationMotion Feature Representationen_US
dc.subject.classificationKinect 3D Skeletonen_US
dc.subject.classificationDynamic Time Warpingen_US
dc.subject.classificationLocal Texture Analysisen_US
dc.titleModel-Based Gait and Action Recognition Using Kinect
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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