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Time-critical adaptive visualization method of 3D city models

The development of hardware and software is not sufficient to meet the real-time visualization requirements of large scale 3D City Models. How to adaptively coordinate the speed and quality of rendering according to the data volume and hardware/software environment is therefore a critical issue. This paper proposes an algorithm which predicts the rendering time according to the features of 3D City Models at first, and then to calculate the object importance value based on the mathematical model which considers the indicators of each object: location, distance, visibility and semantics, and finally to select the object set to be rendered by a fast recursive algorithm. There are five factors selected to test their influence on rendering time: triangle number, vertex number, texture number, screen pixel number, and the texture image size. According to multivariate statistical theory, experimental results prove that both geometry and texture data size are significant for rendering time of 3D City Models. A typical 3D building group models are employed for experimental analysis. The results show that the method introduced in this paper is accurate to predict the time of rendering 3D models with detailed texture. The adaptive rendering performance is also significantly improved.