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Bird’s-eye view image acquisition from simulated scenes using geometric inverse perspective mapping

机译：使用几何逆透视映射从模拟场景拍摄图像获取

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Technology advancement, major investments, and mainstream interest have reignited the prospect of autonomous driving, nevertheless, the achievement of reliable perception is still an active research topic. This article examines a technique for simplifying path planning and control algorithms by reducing spacial dimensions to two, i.e. by acquiring a Bird’s-Eye View (BEV) image. This article aspires to facilitate novel perception fusion approaches by specifying a geometric approach for inverse perspective mapping (IPM), construction of composite BEV of the vehicle, giving suggestions for implementation and proposing a coherent, BEV-based approach for perception fusion. The proposed geometric IPM approach for BEV image acquisition is suited for simulated environments with limited knowledge of the camera’s intrinsic parameters.
机译：技术进步，重大投资和主流利益已经重新培育了自治驾驶的前景，尽管如此，就可以实现可靠的感知仍然是一个积极的研究主题。本文通过获取鸟瞰图（BEV）图像来检查通过减少两个，即通过获取鸟瞰图（BEV）图像来简化路径规划和控制算法的技术。本文旨在通过指定逆透视图（IPM）的几何方法，促进车辆的复合BEV的构造，提出实施建议，提出基于感知融合的相干性，提出一种感知融合的建议，促进新颖的感知融合方法。 BEV图像采集的建议的几何IPM方法适用于模拟环境，了解相机内在参数的有限。

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