A context aware approach for enhancing gesture recognition accuracy on handheld devices

buir.advisorÇapın, Tolga
dc.contributor.authorYıldırım, Hacı Mehmet
dc.date.accessioned2016-01-08T18:14:16Z
dc.date.available2016-01-08T18:14:16Z
dc.date.issued2010
dc.descriptionAnkara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2010.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2010.en_US
dc.descriptionIncludes bibliographical references leaves 75-84.en_US
dc.description.abstractInput capabilities (e.g. joystick, keypad) of handheld devices allow users to interact with the user interface to access the information and mobile services. However, these input capabilities are very limited because of the mobile convenience. New input devices and interaction techniques are needed for handheld devices. Gestural interaction with accelerometer sensor is one of the newest interaction techniques on mobile computing. In this thesis, we introduce solutions that can be used for automatically enhancing the gesture recognition accuracy of accelerometer sensor, and as a standardized gesture library for gestural interaction on touch screen and accelerometer sensor. In this novel solution, we propose a framework that decides on suitable signal processing techniques for acceleration sensor data for a given context of the user. First system recognizes the context of the user using pattern recognition algorithm. Then, system automatically chooses signal ltering techniques for recognized context, and recognizes gestures. Gestures are also standardized for better usage. In this work, we also present several experiments which show the feasibility and e ectiveness of our automated gesture recognition enhancement system.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T18:14:16Z (GMT). No. of bitstreams: 1 0005006.pdf: 1126597 bytes, checksum: 3cadef11ac918085132971357afed91c (MD5)en
dc.description.statementofresponsibilityYıldırım, Hacı Mehmeten_US
dc.format.extentxiii, 84 leaves, illustrationsen_US
dc.identifier.itemidB122708
dc.identifier.urihttp://hdl.handle.net/11693/15153
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGestural interactionen_US
dc.subjectGestureen_US
dc.subjectComputer graphicsen_US
dc.subjectAccelerometer sensoren_US
dc.subjectSignal processingen_US
dc.subject.lccQA76.59 .Y55 2010en_US
dc.subject.lcshMobile computing.en_US
dc.subject.lcshSensor networks.en_US
dc.subject.lcshGesture.en_US
dc.subject.lcshComputer graphics.en_US
dc.subject.lcshThree-dimensional imaging.en_US
dc.subject.lcshSignal processing.en_US
dc.titleA context aware approach for enhancing gesture recognition accuracy on handheld devicesen_US
dc.typeThesisen_US
thesis.degree.disciplineComputer Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
0005006.pdf
Size:
1.07 MB
Format:
Adobe Portable Document Format