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Image Correspondence Using Affine SIFT Flow

机译:使用仿射筛选流的图像对应

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摘要

Image correspondence is one of the critical tasks across various applications of image processing and computer vision. The simple correspondence is being studied from many years for the purpose of image stitching and stereo correspondence. The images assumed for the simple correspondence have same pixel value even after applying the geometric transformations. In this work, we try to correspond images sharing similar content but vary due to change in acquisition like view angle, scale, and illumination. The use of features for flow computation was proposed in SIFT flow, which was used for correspondence across fields. In this method, dense SIFT descriptors are extracted and flow is estimated for matching the SIFT descriptors between two images. In this work, we applied SIFT flow algorithm on the affine transformations of images to be aligned.
机译:图像对应是图像处理和计算机视觉各种应用中的关键任务之一。对于图像拼接和立体对应的目的,从多年进行了简单的对应关系。即使在应用几何变换之后,对于简单对应的图像也具有相同的像素值。在这项工作中,我们尝试对应于相似内容的图像进行对应的图像,而是由于查看角度,比例和照明等获取而变化而变化。在SIFT流中提出了用于流量计算的特征,其用于跨越字段的对应。在该方法中,提取密集的SIFT描述符并估计流程用于匹配两个图像之间的SIFT描述符。在这项工作中,我们应用了在要对齐的图像的仿射变换上应用了Sift流程算法。

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