论文标题
基于非对称双向光流的高质量全景缝线
High-quality Panorama Stitching based on Asymmetric Bidirectional Optical Flow
论文作者
论文摘要
在本文中，我们提出了一种基于非对称双向光流的全景缝制算法。该算法期望Fisheye镜头摄像机捕获的多张照片作为输入，然后通过拟议的算法，可以将这些照片合并为高质量的360度球形全景图像。对于从遥远的角度拍摄的照片，它们中的视差相对较小，并且获得的全景图像几乎可以是无缝且未经证实的。对于从近距离拍摄的照片或以相对较大的视差拍摄的照片，也可以获得无缝扭曲的全景图像。此外，借助图形处理单元（GPU），该算法可以以非常快速的速度完成整个缝制过程：通常，获得9000 x 4000像素的全景图像仅需30秒钟，这意味着我们的Panorama缝制算法在许多实时应用中具有很高的价值。我们的代码可在https://github.com/mungomeng/panorama-optictricflow上找到。
In this paper, we propose a panorama stitching algorithm based on asymmetric bidirectional optical flow. This algorithm expects multiple photos captured by fisheye lens cameras as input, and then, through the proposed algorithm, these photos can be merged into a high-quality 360-degree spherical panoramic image. For photos taken from a distant perspective, the parallax among them is relatively small, and the obtained panoramic image can be nearly seamless and undistorted. For photos taken from a close perspective or with a relatively large parallax, a seamless though partially distorted panoramic image can also be obtained. Besides, with the help of Graphics Processing Unit (GPU), this algorithm can complete the whole stitching process at a very fast speed: typically, it only takes less than 30s to obtain a panoramic image of 9000-by-4000 pixels, which means our panorama stitching algorithm is of high value in many real-time applications. Our code is available at https://github.com/MungoMeng/Panorama-OpticalFlow.
