Hand tracking

dc.contributorGraduate Program in Systems and Control Engineering.
dc.contributor.advisorSankur, Bülent.
dc.contributor.authorDicle, Çağlayan.
dc.date.accessioned2023-03-16T11:34:45Z
dc.date.available2023-03-16T11:34:45Z
dc.date.issued2007.
dc.description.abstractThis thesis presents a hand detection and tracking system where hand is ini- tialized using the color clue and tracking is achieved with the integration of color and texture information. Three nonparametric skin classi cation schemes; histograms, kernel densities, voronoi tessellations are analyzed on six di erent colorspaces. The optimal fusion of color features is also investigated for illumination free skin classi cation. The texture and color cues are combined to track the hand through the course of action. Texture is de ned by Local Binary Patterns (LBP), which is a coarse estimation of joint probability of neighboring pixel values. By combining the color with texture more robust representation of hand is attained and meanshift algorithm is used to locate the hand in this representation space. The results show that texture-color combination can deal with face-hand overlaps and confusions of hand with other skin colored regions..
dc.format.extent30cm.
dc.format.pagesxii, 66 leaves;
dc.identifier.otherSCO 2007 D52
dc.identifier.urihttps://digitalarchive.library.bogazici.edu.tr/handle/123456789/15637
dc.publisherThesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007.
dc.relationIncludes appendices.
dc.relationIncludes appendices.
dc.subject.lcshHuman-computer interaction.
dc.subject.lcshHuman-machine systems.
dc.titleHand tracking

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