Robust camera motion estimation using direct edge alignment and sub-gradient method

Manohar Kuse, S. Shen
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引用次数: 49

Abstract

There has been a paradigm shifting trend towards feature-less methods due to their elegant formulation, accuracy and ever increasing computational power. In this work, we present a direct edge alignment approach for 6-DOF tracking. We argue that photo-consistency based methods are plagued by a much smaller convergence basin and are extremely sensitive to noise, changing illumination and fast motion. We propose to use the Distance Transform in the energy formulation which can significantly extend the influence of the edges for tracking. We address the problem of non-differentiability of our cost function and of the previous methods by use of a sub-gradient method. Through extensive experiments we show that the proposed method gives comparable performance to the previous method under nominal conditions and is able to run at 30 Hz in single threaded mode. In addition, under large motion we demonstrate our method outperforms previous methods using the same runtime configuration for our method.
基于直接边缘对准和次梯度方法的鲁棒摄像机运动估计
由于无特征方法具有优雅的公式、准确性和不断提高的计算能力,因此出现了向无特征方法转变的范式趋势。在这项工作中,我们提出了一种用于六自由度跟踪的直接边缘对准方法。我们认为基于光一致性的方法受到小得多的收敛盆地的困扰,并且对噪声、光照变化和快速运动极其敏感。我们建议在能量公式中使用距离变换,这可以显著地扩展边缘对跟踪的影响。我们通过使用次梯度方法来解决成本函数不可微的问题和前面的方法。通过大量的实验,我们表明所提出的方法在标称条件下具有与先前方法相当的性能,并且能够在单线程模式下以30 Hz的频率运行。此外,在大运动下,我们证明我们的方法优于使用相同运行时配置的先前方法。
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