使用显性知识控制场景重建

R. Tonjes
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引用次数: 3

摘要

景观规划、环境监测、飞行和驾驶模拟器等应用对逼真的景观模型有很高的要求。模型的数量、精度和类型都要求采用基于遥感数据评估的模型生成自动化方法。提出的建模系统AIDA通过集成关于场景中物体外观的先验知识来驱动物体特定的3D重建约束,解决了对高效表示和高真实感的需求。这就需要对场景中的物体进行图像解释,赋予其意义。对于陈述性和程序性知识的显式表示,采用了基于语义网和规则的问题独立形式主义。它提供了数据驱动和模型驱动的控制策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Control of scene reconstruction using explicit knowledge
Applications such as landscape planning, environmental monitoring, and flight and driving simulators have a high demand for realistic landscape models. Quantity, precision and the type of models ask for methods which automate the model generation by evaluation of remote sensing data. The presented modelling system AIDA tackles the demand for efficient representation and high realism by integrating a priori knowledge about the appearance of the objects in the scene to drive object specific constraints for 3D reconstruction. This requires an image interpretation to assign a meaning to the objects in the scene. For explicit representation of the declarative and procedural knowledge a problem independent formalism based on semantic nets and rules is used. It provides both a data driven and model driven control strategy.
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