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Multisensorfusion zur semantisch gestützten Navigation eines autonomen AssistenzrobotersStiene, Stefan 01 July 2009 (has links)
Ein alltagstauglicher autonomer Assistenzroboter in einem gemeinsamenArbeitsumfeld mit dem Menschen erfordert, dass der Roboter sämtliche Hindernisse in seiner Umgebung wahrnimmt und diesen sicher ausweicht. Stand der Technik ist jedoch, dass meist nur 2D-Sensordaten zur Navigation herangezogen werden. Oder es werden3D-Verfahren verwendet, die ausschließlich mit einer speziellen Sensorkonfiguration arbeiten. Diese Arbeit untersucht im Rahmen des LiSA-Projekts wie 3D-Sensordaten effizient und flexibel zur sicheren Navigation eines autonomenAssistenzsystems eingesetzt werden können. Dazu wird in dieser Arbeit mit der Virtual Range Scans (VRS)-Methode ein Verfahren zurHindernisvermeidung entwickelt, das beliebige Konfigurationen von Abstandssensoren in den Hindernisvermeidungsprozess integriert. Das Verfahren nutztklassische Verfahren zur 2D-Hindernisvermeidung, um 3D-Hindernisvermeidung zu realisieren. Dadurch wird das VRS-Verfahren unabhängig von der Hindernisvermeidungsstrategie und kann flexibel bestehende Verfahren wiederverwenden. Neben der Hindernisvermeidung wird gezeigt, wie die reichereUmgebungsinformation, die in 3D-Sensordaten vorhanden ist, zur robusteren Selbstlokalisierung des Roboters genutzt werden kann. Hier wird eineffizientes Verfahren vorgestellt, das Abstandssensordaten mit 3D-Umgebungsmodellen vergleicht. Ferner wird ein Verfahren vorgestellt, das Semantikim Umfeld des Roboters verankert und sie zur Navigation des Roboters nutzt.
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3-D Model Characterization and Identification from Intrinsic LandmarksCamp, John L. 07 December 2011 (has links)
No description available.
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Automatic 3D facial modelling with deformable modelsXiang, Guofu January 2012 (has links)
Facial modelling and animation has been an active research subject in computer graphics since the 1970s. Due to extremely complex biomechanical structures of human faces and people’s visual familiarity with human faces, modelling and animating realistic human faces is still one of greatest challenges in computer graphics. Since we are so familiar with human faces and very sensitive to unnatural subtle changes in human faces, it usually requires a tremendous amount of artistry and manual work to create a convincing facial model and animation. There is a clear need of developing automatic techniques for facial modelling in order to reduce manual labouring. In order to obtain a realistic facial model of an individual, it is now common to make use of 3D scanners to capture range scans from the individual and then fit a template to the range scans. However, most existing template-fitting methods require manually selected landmarks to warp the template to the range scans. It would be tedious to select landmarks by hand over a large set of range scans. Another way to reduce repeated work is synthesis by reusing existing data. One example is expression cloning, which copies facial expression from one face to another instead of creating them from scratch. This aim of this study is to develop a fully automatic framework for template-based facial modelling, facial expression transferring and facial expression tracking from range scans. In this thesis, the author developed an extension of the iterative closest points (ICP) algorithm, which is able to match a template with range scans in different scales, and a deformable model, which can be used to recover the shapes of range scans and to establish correspondences between facial models. With the registration method and the deformable model, the author proposed a fully automatic approach to reconstructing facial models and textures from range scans without re-quiring any manual interventions. In order to reuse existing data for facial modelling, the author formulated and solved the problem of facial expression transferring in the framework of discrete differential geometry. The author also applied his methods to face tracking for 4D range scans. The results demonstrated the robustness of the registration method and the capabilities of the deformable model. A number of possible directions for future work were pointed out.
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