Tag-less feature based tangible detection and tracking using custom gestures

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dc.contributor.advisorMaurer, Frank Oliver
dc.contributor.authorShouman, Maha
dc.date.accessioned2017-12-18T22:28:59Z
dc.date.available2017-12-18T22:28:59Z
dc.date.issued2012
dc.descriptionBibliography: p. 89-94en
dc.description.abstractDigital tabletops have gained prominence in research and industry, as they support new types of interaction, such as tangible user interfaces. The task of tangible detection and tracking is generally accomplished through using tags to mark the objects, or by forwarding information on the objects to developers, who do the identification and tracking. This thesis presents a methodology and toolkit through which tag-less object detection can be achieved, by using a feature-based computer vision algorithm. This allows developers to access their tangibles through the names that they provide and protects them from the complexities of computer vision algorithms and the tracking of tangibles. It also allows for the integration of multi-touch and tangible interaction, as both modalities are crucial to communicating with digital tabletops. Custom gestures can be defined which encompass touches and tangibles. A user study was conducted which demonstrated that participants found the toolkit to be useful and easy to use.
dc.format.extentxii, 102 leaves : ill. ; 30 cm.en
dc.identifier.citationShouman, M. (2012). Tag-less feature based tangible detection and tracking using custom gestures (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/4623en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/4623
dc.identifier.urihttp://hdl.handle.net/1880/105624
dc.language.isoeng
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.titleTag-less feature based tangible detection and tracking using custom gestures
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
ucalgary.thesis.accessionTheses Collection 58.002:Box 2077 627942921
ucalgary.thesis.notesUARCen
ucalgary.thesis.uarcreleaseyen
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