ACT-CORNER: Active corner finding for optic flow determination

G. D. Croon, S. Nolfi
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引用次数: 4

Abstract

A highly efficient corner finding algorithm, named ACT-CORNER, is introduced. The algorithm uses active sub-sampling: it searches for corners by exploiting information from local image samples. ACT-CORNER is compared to both the Harris and FAST corner detectors. It is computationally much more efficient than the Harris corner detector. The comparison with FAST depends on the image size, with an advantage for ACT-CORNER for image dimensions of 320 × 240 pixels or larger. ACT-CORNER's performance is evaluated in the context of optic flow based Time-To-Contact (TTC) estimation. Image zoom experiments show that the accuracy of TTC estimations is similar when ACT-CORNER or FAST are used for corner detection. Finally, experiments with a Parrot AR drone show that the TTC estimates based on ACT-CORNER correspond well to sonar-based estimates.
ACT-CORNER:用于光流测定的主动角查找
介绍了一种高效的角点查找算法ACT-CORNER。该算法采用主动子采样,利用局部图像样本中的信息寻找角点。ACT-CORNER与Harris和FAST拐角探测器进行了比较。它的计算效率比哈里斯角探测器高得多。与FAST的比较取决于图像尺寸,ACT-CORNER的优势在于图像尺寸为320 × 240像素或更大。ACT-CORNER的性能在基于光流的接触时间(TTC)估计的背景下进行评估。图像缩放实验表明,采用ACT-CORNER或FAST进行角点检测时TTC估计的精度相似。最后,用Parrot AR无人机进行的实验表明,基于ACT-CORNER的TTC估计与基于声纳的估计很好地对应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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