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Integration of Hough Transform of lines and planes in the framework of conformal geometric algebra for 2D and 3D robot vision

机译:在2D和3D机器人视觉的保形几何代数框架中整合线和平面的Hough变换

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This paper presents the application of 2D and 3D Hough Transforms together with conformal geometric algebra to build 3D geometric maps using the geometric entities of lines and planes. Among several existing techniques for robot self-localization, a new approach is proposed for map matching in the Hough domain. The geometric Hough representation is formulated in such a way that one can easily relate it to the conformal geometric algebra framework; thus, the detected lines and planes can be used for algebra-of-incidence computations to find geometric constraints, useful when perceiving special configurations in 3D visual space for exploration, navigation, relocation and obstacle avoidance. We believe that this work is very useful for 2D and 3D geometric pattern recognition in robot vision tasks.
机译:本文介绍了2D和3D Hough变换与共形几何代数一起使用线和平面的几何实体构建3D几何图的应用。在机器人自定位的几种现有技术中,提出了一种用于Hough域中地图匹配的新方法。几何霍夫表示法的制定方式使人们可以轻松地将其与共形几何代数框架联系起来。因此,检测到的线和平面可用于入射角的代数计算,以找到几何约束,这对于在3D视觉空间中感知特殊配置以进行探索,导航,重新定位和避障而言非常有用。我们相信这项工作对于机器人视觉任务中的2D和3D几何图案识别非常有用。

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