Computer interfaces using vision based gesture recognition

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dc.contributor.advisorParker, James R.
dc.contributor.authorBaumback, Mark
dc.date.accessioned2005-08-16T17:22:15Z
dc.date.available2005-08-16T17:22:15Z
dc.date.issued2004
dc.descriptionBibliography: p. 138-150en
dc.description.abstractThe primary objective of this thesis is to obtain information from a non-instrumented hand - including precise points of contact between the real hand and the virtual environment, and the recognition of meaningful hand postures - so that they can be used to replace standard input devices. Two different methods are presented in this thesis, ERSolitaire and finger classification, which recognize hand postures for use in a natural interface. ERSolitaire provides a grab-move-release interface to the standard game of solitaire, which allows the user to interact with virtual cards in a similar fashion as they would with real cards. The finger classification system provides a virtual touch interface by individually recognizing each of the five fingers. This provides greater power and flexibility than other similar systems, as well as a new technique for hand posture recognition.en
dc.format.extentx, 150 leaves : ill. ; 30 cm.en
dc.identifier.citationBaumback, M. (2004). Computer interfaces using vision based gesture recognition (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/17037en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/17037
dc.identifier.isbn0612976327en
dc.identifier.lccAC1 .T484 2004 B3798en
dc.identifier.urihttp://hdl.handle.net/1880/41950
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.titleComputer interfaces using vision based gesture recognition
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 1488 520492005
ucalgary.thesis.notesUARCen
ucalgary.thesis.uarcreleaseyen
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