The Perceptual LOD System based on the Recognition Prototypes of Models

Level-of-detail (LOD) is one of the significant techniques which widely applied in the field of computer graphics. LOD is a kind of technique that a mesh of 3D model is simplified according to the distance between viewer and model in a scene. We combine Human Perceptual System to our LOD research in order to using human’s reorganization of sight to retain model’s characteristic for simplifying model. It makes simplified models more identifiable.

In this research, we implemented our perceptual LOD system based on the QEM algorithm. The traditional methods reduce the complexity of model gradually until there is no surface left, mainly based on the geometric consideration. Therefore, we proposed our perceptual LOD system by modifying the mesh simplification sequence of QEM and adopting the concept of Human Perceptual System.

In order to further improve our perceptual LOD system, by extracting and analyzing the possible prototype from multiple related models, the cognitive prototypes in human perceptual system (HPS) are constructed. Our central idea is to maintain the object visually recognizable during the model simplification stage, by reserving the important features according to the characteristics of the cognitive prototype.

In addition, we take the size of projection area, which influence model’s level of detail, into consideration. The area has influence on user’s recognizing ability for model. Finally, we use the weighting values which are determined from the prototypes to improve the simplifying strategy. With the proposed method, we can preserve the important features of HPS while model is simplified, so the simplified model can remain recognizable under lower LOD.

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