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Robust motion estimation methods using gradient orientation information

机译:使用梯度方向信息的鲁棒运动估计方法

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摘要

Changing lighting conditions cause temporal variations of image intensities and make most existing motion estimation techniques ineffective. As a solution to this problem, we use gradient orientation information, which depends very little on changes of image intensities, in place of commonly used image features such as intensities and gradients. By employing gradient orientation, two conventional motion estimation techniques (the spatio-temporal gradient method and the gradient structure tensor method) can be transformed into methods that are far more robust to changing image intensities. Simulation results on both synthetic and real image sequences show that the proposed methods perform motion estimation remarkably well irrespective of time-varying image intensities. In addition, the proposed methods also cope better with the aperture problem in which only unidirectional gradients are available and large erroneous motion estimates are produced
机译:不断变化的照明条件会导致图像强度随时间变化,并使大多数现有的运动估计技术无效。为了解决这个问题,我们使用了梯度方向信息,该信息几乎不依赖于图像强度的变化,而代替了诸如强度和梯度之类的常用图像特征。通过采用梯度方向,可以将两种常规的运动估计技术(时空梯度方法和梯度结构张量方法)转换为对改变图像强度更鲁棒的方法。在合成图像序列和真实图像序列上的仿真结果均表明,所提出的方法可以很好地执行运动估计,而与时变图像强度无关。另外,所提出的方法还更好地解决了孔径问题,在孔径问题中,仅单向梯度可用,并且产生了大的错误运动估计。

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