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Randomized Hough transform applied to translational and rotational motion analysis

机译:随机霍夫变换在平移和旋转运动分析中的应用

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A method has been developed to calculate 2-D motion in a sequence of time-varying images. The method, called motion detection using randomized Hough transform (MDRHT), is based on the randomized Hough transform (RHT). The RHT decreases considerably the time consumption and memory requirements of the Hough transform. The idea of the MDRHT is to pick randomly point pairs from two images and calculate the translation with them. The points can be e.g. edge points of the original images. This approach can avoid difficulties of standard segmentation methods like overlapping and covering, and has the advantages provided by the RHT. The method can be generalized by picking more than two points. After a brief review of the RHT applied to motion detection, the extended algorithm to calculate both translation and rotation is represented in this paper.
机译:已经开发出一种方法来计算随时间变化的图像序列中的二维运动。该方法称为使用随机霍夫变换(MDRHT)的运动检测,该方法基于随机霍夫变换(RHT)。 RHT大大减少了霍夫变换的时间消耗和内存需求。 MDRHT的想法是从两个图像中随机选择点对,然后计算它们的平移。这些点可以是例如原始图像的边缘点。这种方法可以避免诸如重叠和覆盖之类的标准分割方法的困难,并且具有RHT提供的优点。可以通过选择两个以上的点来概括该方法。在简要回顾了应用于运动检测的RHT之后,本文介绍了用于计算平移和旋转的扩展算法。

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