Traditional image stitching focuses on a single panorama frame without considering the spatial-temporal consistency in videos. The straightforward image stitching approach will cause temporal flicking and color inconstancy when it is applied to the video stitching task. Besides, inaccurate camera parameters will cause artifacts in the image warping. In this paper, we propose a real-time system to stitch multiple video sequences into a panoramic video, which is based on GPU accelerated color correction and frame warping without accurate camera parameters. We extend the traditional 2D-Matrix (2D-M) color correction approach and a present spatio-temporal 3D-Matrix (3D-M) color correction method for the overlap local regions with online color balancing using a piecewise function on global frames. Furthermore, we use pairwise homography matrices given by coarse camera calibration for global warping followed by accurate local warping based on the optical flow. Experimental results show that our system can generate highquality panorama videos in real time.

翻译：传统图像拼接技术侧重于单帧全景图的生成，未能考虑视频中的时空一致性。将这种直接式图像拼接方法应用于视频拼接任务时，会导致时间闪烁和色彩不一致问题。此外，相机参数的不精确会引起图像映射中的伪影。本文提出一种基于GPU加速的色彩校正与帧映射实时系统，无需精确相机参数即可将多路视频序列拼接为全景视频。我们扩展了传统2D矩阵（2D-M）色彩校正方法，提出一种面向重叠局部区域的时空三维矩阵（3D-M）色彩校正方法，并采用全局帧的分段函数实现在线色彩平衡。进一步，利用粗标定得到的成对单应性矩阵进行全局映射，再结合光流法实现精确的局部映射。实验结果表明，本系统能够实时生成高质量的全景视频。