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A direct method on camera's ego-motion estimation using normal flows

机译:使用正常流的摄像机自我运动估计的直接方法

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In this paper, we propose a novel method to estimate the camera's ego-motion parameters by directly using the normal flows. Normal flows, the projection of the optical flows along the direction of the gradient of image intensity, could be calculated directly from the image sequence without any artificial assumptions about the captured scene. Different from many traditional approaches which tackle the problem by establishing motion correspondences or by estimating optical flows, our proposed method could obtain the motion parameters directly by using the information of spatio-temporal gradient of the image intensity. Hence, our method requires no specific assumptions about the captured scene, such as the smoothness constraint, continuity constraint, distinct features appearing in the scene and etc.. Our method has been experimentally tested by using both synthetic image data and real image sequences. The experimental results demonstrate that our proposed method is feasible and reliable.
机译:在本文中,我们提出了一种新颖的方法来通过直接使用正常流来估计相机的自我运动参数。正常流动,光学流的投影沿图像强度的梯度方向,可以直接从图像序列计算,而没有任何关于捕获场景的人工假设。通过建立运动对应关系或通过估计光学流来解决问题的许多传统方法不同,我们所提出的方法可以通过使用图像强度的时空梯度的信息直接获得运动参数。因此,我们的方法不需要关于捕获的场景的具体假设,例如平滑度约束,场景中出现的不同特征等。我们的方法已经通过使用合成图像数据和真实图像序列进行了实验测试。实验结果表明,我们所提出的方法是可行可靠的。

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