Strategies for Model Simplification and Data Reduction in Holographic Virtual Prototyping and Product Visualization Through Application Dependent Model Pre-Processing

Abstract

Three-dimensional (3D) displays are increasingly becoming common output devices for design support systems. They are widely used in applications such as virtual prototyping e.g. for visualization of product data and for concepts demonstration. Holographic displays are among the visualization devices that are capable of generating suitable 3D virtual models for these kinds of applications. However, these displays typically require powerful computers for processing and rendering large amount of volumetric data. Large amount of data in holographic displays and in volumetric displays in general often causes rendering delay, i.e. slow response to users’ actions and slow interaction speed. These problems, along with the problem of insufficient display resolution, have historically prevented 3D volumetric visualization technologies like holographic displays from becoming the mainstream product visualization means. In general terms, visualization of volumetric data requires sophisticated and efficient rendering methods that take the amount of data into account. In this paper, we introduce and discuss rigorous strategies for model simplification and data reduction in holographic display based virtual prototyping processes. Data reduction is achieved through model simplification; which involves identification of visualization demands for the application at hand and tailoring the model to meet these demands. We first briefly review the methods traditionally used in reducing computing resource requirements and then we propose strategies for lowering the amount of data in holographic virtual prototyping while keeping the displayed virtual model relevant to the visualization demands at hand. We also demonstrate by using practical examples the significance of the proposed strategies and how they can be used in practical settings. The proposed approach is configurable and scalable. It has been demonstrated in this work that its underlying algorithms can reduce computation burden in holographic displays and instigate swift computing by letting the display process information tailored specifically for particular visualization demands.