Automatic panoramic image stitching using invariant features
Automatic panoramic image stitching using invariant features
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DOI：
10.1007/s11263-006-0002-3
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发表时间：
2007-08-01
影响因子：
19.5
通讯作者：
Lowe, David G.
中科院分区：
文献类型：
--
作者：
Brown, Matthew;Lowe, David G.
本文涉及全自动全景图像缝合的问题。尽管对ID问题（旋转的单轴）进行了充分的研究，但2D或多行缝线更加困难。以前的方法已使用人类输入或对图像序列的限制来建立匹配的图像。在这项工作中，我们将缝线制定为多图像匹配问题，并使用不变的本地功能来查找所有图像之间的匹配。因此，我们的方法对输入图像的排序，方向，扩展和照明不敏感。它对不是全景图的噪声图像也不敏感，并且可以识别无序图像数据集中的多个全景图。除了提供更多细节外，本文还通过引入增益补偿和自动拉直步骤来扩展我们以前在该地区的工作（Brown and Lowe，2003）。
This paper concerns the problem of fully automated panoramic image stitching. Though the ID problem (single axis of rotation) is well studied, 2D or multi-row stitching is more difficult. Previous approaches have used human input or restrictions on the image sequence in order to establish matching images. In this work, we formulate stitching as a multi-image matching problem, and use invariant local features to find matches between all of the images. Because of this our method is insensitive to the ordering, orientation, scale and illumination of the input images. It is also insensitive to noise images that are not part of a panorama, and can recognise multiple panoramas in an unordered image dataset. In addition to providing more detail, this paper extends our previous work in the area (Brown and Lowe, 2003) by introducing gain compensation and automatic straightening steps.