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Sparse line-optical flow field computing method based on lines Matching

机译:基于线匹配的稀疏线路光流场计算方法

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This paper brings out a new sparse line-optical flow field computing method. Firstly, we establish a lines matching algorithm based on Kalman Filter (KF). In this algorithm, we map lines in an image into Hough space, after that we employ KF to predict the position in the following frame in order to match lines in image sequence. Secondly, we present the concept of sparse line-optical flow field of images and propose the calculation method of it. By using the camera perspective projection model and the optical flow Identity, we can get the sparse line-optical flow field. Simulations is made in the following step, and results show that the lines matching algorithm works well and the accuracy of the calculation method proposed in this paper is as good as that of the classic Horn algorithm, while the calculating time-cost of it is only 1/30 Horn algorithm's.
机译:本文提出了一种新的稀疏线路光流场计算方法。首先,我们建立了一种基于卡尔曼滤波器(KF)的线匹配算法。在该算法中,我们将图像中的线映射到Hough Space中,之后我们使用KF来预测以下帧中的位置,以便在图像序列中匹配线路。其次,我们介绍了稀疏线路光流场的概念,并提出了它的计算方法。通过使用相机透视投影模型和光学流量标识,我们可以获得稀疏线路光流场。在以下步骤中进行了模拟,结果表明,线路匹配算法运行良好,本文提出的计算方法的准确性与经典喇叭算法一样好,而计算的计算时间成本也是良好的1/30喇叭算法。

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