顾及场景复杂度的三维模型与地形匹配方法研究

Matching Method of 3D Model and Terrain Considering Scene Complexity

  • 摘要: 三维场景中三维模型与地形模型进行匹配时存在缝隙或地形淹没模型等问题,导致三维场景可视化效果不佳,难以满足风险监测、精细测量等领域的应用需求。针对该问题,提出了顾及场景复杂度的三维模型与地形模型匹配方法,解决了模型与地形之间的匹配问题。首先,结合三维模型特性改进了多源异构三维模型数据组织;然后,结合模型数据组织方案构建了三维场景复杂度评估模型;最后,在不同场景复杂度下,实现了顾及场景复杂度的多源异构三维模型与地形的精确匹配。研究结果表明,所提方法在保证三维模型渲染时实时帧率的同时,切实优化模型与地形之间的精确匹配问题,满足了多尺度观察三维场景要素及目视精确定位的要求。

     

    Abstract:
    Objectives In 3 dimensional (3D) scenes, the bottom surface of 3D models is usually horizontal, and terrain models are mostly irregular surfaces with continuous undulations, which leads to problems such as gaps or terrain flooding when matching 3D models with terrain models, etc. In the current research on matching 3D models with terrain, there is a lack of scene complexity constraint, so some matching methods are not applicable to 3D scenes with multiple complexities. Therefore, how to complete model-terrain matching while taking into account the scene complexity constraint and retaining certain terrain integrity is the current problem to be considered and solved.
    Methods Through research on 3D model data organization, scene complexity evaluation, and grid reconstruction, etc., a 3D model and terrain model matching method that takes into account the scene complexity is proposed to achieve a seamless matching between the model and the terrain. First, the method improves the data organization of multi-source heterogeneous 3D model by combining the characteristics of 3D model. Then, it constructs the 3D scene complexity evaluation model by combining the scene complexity evaluation factors, and calculates and classifies the 3D scene complexity level. Finally, according to the scene complexity classification results, it realizes the accurate matching of multi-source heterogeneous 3D models and terrain considering the scene complexity.
    Results Different 3D scenes contain different amounts of information, and their corresponding scene complexity is also different. For the 3D scenes with low scene complexity, the elevation value fitting method is used, and the 3D scenes with high scene complexity use the grid reconstruction method. The visual perception and real-time frame rate are used as reference indicators to compare and analyze this method with the traditional method. The frame rate is stable at 58 frames per second, and it can be seen that the scene complexity constraint of this method can optimize the system loading smoothness and improve the visualization effect.
    Conclusion We construct a scene complexity evaluation model based on scene information entropy, and design a model and terrain adaptation algorithm adapted to the scene complexity level. We organize and express the 3D scene model data with different scene complexity more efficiently while ensuring the real-time frame rate when rendering the 3D model, and effectively optimizes the problem of accurate matching between model and terrain.

     

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