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Evaluation of feature based image stitching algorithm using OpenCV

机译:使用OpenCV评估基于特征的图像拼接算法

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Image stitching is an attractive method to merging multiple images. It can produce a wide-angle panoramic photograph while maintaining the quality of the source images. The process is simply performed by overlapping part of the images which contain common scene. Today, panoramic image stitching is widely used in applications such as 360-degree cameras and virtual reality photography. If the stitching technology ensure fast processing speed and accurate performance, it is expected to produce diverse image contents in real time. Moreover, the panoramic images can be mapped to various projective layouts, e.g. spherical and stereographic projection. The mapping of the panoramic image along the suitable projective layout makes it possible to express more stereoscopic space, that is, the space in the photo can give the impression that it looks as if it is in front. It can be utilized when creating 3D reconstruction space with high-resolution panoramic images. This paper describes the concept of feature based image stitching and presents the implementation results. It also provides the results of stitching with more than 10 images and suggests the time-efficient way for stitching multiple images. The time-efficient stitching method can be applied to various applications so that panoramic images can be easily accessed in everyday life.
机译:图像拼接是合并多个图像的一种有吸引力的方法。它可以产生广角全景照片,同时保持源图像的质量。简单地通过重叠包含共同场景的部分图像来执行该过程。如今,全景图像拼接已广泛用于360度相机和虚拟现实摄影等应用中。如果缝合技术可确保快速的处理速度和准确的性能,则可以实时产生各种图像内容。而且,全景图像可以被映射到各种投影布局,例如。球形和立体投影。全景图像沿着适当的投影布局的映射可以表达更多的立体空间,也就是说,照片中的空间可以给人以看起来像在前面的印象。在创建具有高分辨率全景图像的3D重建空间时可以使用它。本文介绍了基于特征的图像拼接的概念,并给出了实现结果。它还提供了多于10幅图像的拼接结果,并提出了拼接多幅图像的省时方法。省时的拼接方法可以应用于各种应用,因此在日常生活中可以轻松访问全景图像。

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