Efficient Line and Patch Feature Characterization and Management for Real-time Camera Tracking

dc.contributor.authorWuest, Haralden_US
dc.coverage.spatialTechnische Universitaet Darmstadten_US
dc.date.accessioned2015-01-21T06:49:08Z
dc.date.available2015-01-21T06:49:08Z
dc.date.issued2008en_US
dc.description.abstractOne of the key problems of augmented reality is the tracking of the camera position andviewing direction in real-time. Current vision-based systems mostly rely on the detectionand tracking of fiducial markers. Some markerless approaches exist, which are based on3D line models or calibrated reference images. These methods require a high manualpreprocessing work step, which is not applicable for the efficient development and designof industrial AR applications.The problem of the preprocessing overload is addressed by the development of vision-basedtracking algorithms, which require a minimal workload of the preparation of referencedata.A novel method for the automatic view-dependent generation of line models in real-timeis presented. The tracking system only needs a polygonal model of a reference object,which is often available from the industrial construction process. Analysis-by-synthesistechniques are used with the support of graphics hardware to create a connection betweenvirtual model and real model.Point-based methods which rely on optical flow-based template tracking are developedfor the camera pose estimation in partially known scenarios. With the support of robustreconstruction algorithms a real-time tracking system for augmented reality applicationsis developed, which is able to run with only very limited previous knowledge about thescene. The robustness and real-time capability is improved with a statistical approach fora feature management system which is based on machine learning techniques.IIIen_US
dc.formatapplication/pdfen_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/8207
dc.languageEnglishen_US
dc.publisherWuesten_US
dc.titleEfficient Line and Patch Feature Characterization and Management for Real-time Camera Trackingen_US
dc.typeText.PhDThesisen_US
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