We propose to rely on the wave equation for the detection of repeatable keypoints invariant up to image scale and rotation and robust to viewpoint variations, blur, and lighting changes. The algorithm exploits the properties of local spatial–temporal extrema of the evolution of image intensities under the wave propagation to highlight salient symmetries at different scales. Although the image structures found by most state-of-the-art detectors, such as blobs and corners, occur typically on highly textured surfaces, salient symmetries are widespread in diverse kinds of images, including those related to poorly textured objects, which are hardly dealt with by current pipelines based on local invariant features. The impact on the overall algorithm of different numerical wave simulation schemes and their parameters is discussed, and a pyramidal approximation to speed-up the simulation is proposed and validated. Experiments on publicly available datasets show that the proposed algorithm offers state-of-the-art repeatability on a broad set of different images while detecting regions that can be distinctively described and robustly matched.

中文翻译：

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通过波传播进行关键点检测

我们建议依靠波动方程来检测可重复的关键点，这些关键点在图像范围和旋转范围内是不变的，并且对于视点变化，模糊和照明变化具有鲁棒性。该算法利用了波传播下图像强度演化的局部时空极值特性，以突出显示不同尺度下的显着对称性。尽管大多数先进的检测器（例如斑点和拐角）发现的图像结构通常出现在高度纹理化的表面上，但显着的对称性在各种图像中均很普遍，包括与质地较差的对象有关的图像，这些图像几乎很难当前的管道基于局部不变特征处理。讨论了不同数值波模拟方案及其参数对整体算法的影响，提出并验证了金字塔近似以加快仿真速度。在公开可用数据集上进行的实验表明，该算法在检测不同区域时可以提供最先进的可重复性，同时还能检测出可以分别描述和鲁棒匹配的区域。