文件名称:
Automatic Panoramic Image Stitching using Invariant Features
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上传时间: 2016-04-23
详细说明： Automatic Panoramic Image Stitching using Invariant Features MATTHEW BROWN∗ AND DAVID G. LOWE Department of Computer Science, University of British Columbia, Vancouver, Canada mbrown@cs.ubc.ca lowe@cs.ubc.ca Received July 28, 2005; Accepted August 3, 2006 First online version published in December, 2006 Abstract. This paper concerns the problem of fully automated panoramic image stitching. Though the 1D 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. Keywords: multi-image matching, stitching, recognition ...展开收缩
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