Product visualization in AR/VR applications requires a largely manual process of data preparation. Previous publications focus on error-free triangulation or transformation of product structure data and display attributes for AR/VR applications. This paper focuses on the preparation of the required geometry data. In this context, a significant reduction in effort can be achieved through automation. The steps of geometry preparation are identified and examined concerning their automation potential. In addition, possible couplings of sub-steps are discussed. Based on these explanations, a structure for the geometry preparation process is proposed. With this structured preparation process, it becomes possible to consider the available computing power of the target platform during the geometry preparation. The number of objects to be rendered, the tessellation quality, and the level of detail can be controlled by the automated choice of transformation parameters. Through this approach, tedious preparation tasks and iterative performance optimization can be avoided in the future, which also simplifies the integration of AR/VR applications into product development and use. A software tool is presented in which partial steps of the automatic preparation are already implemented. After an analysis of the product structure of a CAD file, the transformation is executed for each component. Functions implemented so far allow, for example, the selection of assemblies and parts based on filter options, the transformation of geometries in batch mode, the removal of certain details, and the creation of UV maps. Flexibility, transformation quality, and timesavings are described and discussed.
AR/VR applications are a valuable tool in product development and the overall product lifecycle in engineering. However, data transformation of the models from CAD systems to the AR/VR applications is labor-intensive and requires expertise. The main task in the data transformation is the tessellation of the product geometry. Depending on the product complexity and the performance of the target platform extensive optimization is needed to ensure the usability and visual quality of the AR/VR application. Current approaches to this problem use iterative and inflexible processes mostly based on tessellation and on mesh decimation that ignore the varying importance of different geometric aspects for an AR/VR application. An alternative respectively more targeted approach is proposed, that aims at predicting tessellation results and moving the optimization process before the actual tessellation. As a result, the need for iterative operations on the polygon meshes can be reduced or ideally avoided altogether. The paper presents some results of an investigation of the hypothesis that geometric complexity metrics can be used to control and enhance the choice of tessellation parameters. Several characteristics and metrics are identified and gathered from literature and subsequently evaluated with regard to the polygon count and visual quality in the geometry preparation process. Based on the evaluation, prediction models are created and implemented in a geometry preparation tool. The performance is evaluated and discussed.
AR/VR applications are a valuable tool in product design and lifecycle. But the integration of AR/VR is not seamless, as CAD models need to be prepared for the AR/VR applications. One necessary data transformation is the tessellation of the analytically described geometry. To ensure the usability, visual quality and evaluability of the AR/VR application, time consuming optimisation is needed depending on the product complexity and the performance of the target device.Widespread approaches to this problem are based on iterative mesh decimation. This approach ignores the varying importance of geometries and the required visual quality in engineering applications. Our predictive approach is an alternative that enables optimisation without iterative process steps on the tessellated geometry.The contribution presents an approach that uses surface-based prediction and enables predictions of the perceived visual quality of the geometries. This contains the investigation of different geometric complexity metrics gathered from literature as basis for prediction models. The approach is implemented in a geometry preparation tool and the results are compared with other approaches.
Product visualization in AR/VR applications requires a largely manual process of data preparation. Previous publications focus on error-free triangulation or transformation of product structure data and display attributes for AR/VR applications. This paper focuses on the preparation of the required geometry data. In this context, a significant reduction in effort can be achieved through automation. The steps of geometry preparation are identified and examined with respect to their automation potential. In addition, possible couplings of sub-steps are discussed. Based on these explanations, a structure for the geometry preparation process is proposed. With this structured preparation process it becomes possible to consider the available computing power of the target platform during the geometry preparation. The number of objects to be rendered, the tessellation quality and the level of detail can be controlled by the automated choice of transformation parameters. We present a software tool in which partial steps of the automatic preparation are already implemented. After an analysis of the product structure of a CAD file, the transformation is executed for each component. Functions implemented so far allow, for example, the selection of assemblies and parts based on filter options, the transformation of geometries in batch mode, the removal of certain details and the creation of UV maps. Flexibility, transformation quality and time savings are described and discussed.
Die Produktvisualisierung in AR/VR-Anwendungen erfordert einen weitgehend manuellen Prozess der Datenaufbereitung. Bisherige Veröffentlichungen konzentrieren sich auf die fehlerfreie Triangulation oder Transformation von Produktstrukturdaten und Anzeigeattributen für AR/VR-Anwendungen. Diese Arbeit konzentriert sich auf die Aufbereitung der benötigten Geometriedaten. In diesem Zusammenhang kann durch Automatisierung eine deutliche Aufwandsreduzierung erreicht werden. Die Schritte der Geometrieaufbereitung werden identifiziert und auf ihr Automatisierungspotenzial hin untersucht. Darüber hinaus werden mögliche Kopplungen von Teilschritten diskutiert. Es wird eine Struktur für den Geometrieaufbereitungsprozess vorgeschlagen. Mit diesem strukturierten Prozess wird es möglich, die verfügbare Rechenleistung der Zielplattform bei der Geometrieaufbereitung zu berücksichtigen. Die Anzahl der zu rendernden Objekte, die Qualität der Tesselierung und der Detailgrad können durch die automatisierte Wahl der Transformationsparameter gesteuert werden. Es wird ein Software-Tool vorgestellt, in dem Teile der automatischen Aufbereitung bereits implementiert sind. Nach einer Analyse der Produktstruktur einer CAD-Datei wird die Transformation für jede Komponente (Bauteil oder Baugruppe) durchgeführt. Bisher implementierte Funktionen erlauben z.B. die Auswahl von Komponenten anhand von Filteroptionen, die Transformation im Batch-Modus, das Entfernen bestimmter Details und die Erstellung von UV-Maps. Flexibilität, Transformationsqualität und Zeitersparnis werden beschrieben und diskutiert.
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