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The implementation of contour-based object orientation estimation algorithm in FPGA-based on-board vision system

机译:基于轮廓的目标定向估计算法在基于FPGA的车载视觉系统中的实现

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This paper describes the implementation of the orientation estimation algorithm in FPGA-based vision system. An approach to estimate an orientation of objects lacking axial symmetry is proposed. Suggested algorithm is intended to estimate orientation of a specific known 3D object based on object 3D model. The proposed orientation estimation algorithm consists of two stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A3 80. The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.
机译:本文介绍了基于FPGA的视觉系统中方向估计算法的实现。提出了一种估计缺乏轴向对称性的物体的方向的方法。建议的算法旨在基于对象3D模型估计特定已知3D对象的方向。所提出的方向估计算法包括两个阶段:学习和估计。学习阶段致力于被研究对象的探索。使用3D模型,我们可以通过从均匀分布在球体上的视点捕获3D模型来收集训练图像集。球点分布是根据地层原理进行的。收集的训练图像集用于计算描述符,该描述符将在算法的估计阶段使用。估计阶段着重于观察图像描述符和训练图像描述符之间的匹配过程。使用一组空中客车A3 80的图像进行了实验研究。所提出的方向估计算法在所有案例研究中均显示出良好的准确性。演示了该算法在基于FPGA的视觉系统中的实时性能。

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