多摄像机下动态前景分离的视频拼接算法

Multi-camera Video Stitching Based on Foreground Extraction

针对多摄相机固定拍摄的条件,提出一种新的动态前景分离的视频拼接算法,该算法主要解决了视频中运动物体所导致的匹配错误以及可能产生的拼接鬼影现象.首先提取视频的背景图像并分离前景,利用一套自动配准的算法对背景图像进行配准得到匹配关系,进而建立大场景背景视频;提取动态前景并计算在视频重叠区域中的前景目标的匹配度以判断2视频中目标是否为同一物体,重新取舍并补回背景视频中,从而避免了直接拼接所引发的鬼影现象.实验结果表明,该视频拼接算法匹配精度高、鲁棒性强、视频流畅、计算效率高并基本达到实时拼接的效果.

This paper presents an automatic methodology to stitch muhiple videos from different views together based on foreground extraction. Although video stitching technique has been studied by many researchers, the stitching results are still limited by the challenges caused by the moving objects, especially the foregrounds that are notably close to the cameras. The method was mainly concerned with the inaccurate registration and the stitching ghost caused by the moving foreground in the videos. The background frames of the videos were extracted and registered to find out the correlation between them. The moving objects that were separated from the background frames were sent to a different function to find out whether the objects from different videos represented the same one cau objects were then chosen as block to be mosaiced back or dissolved to avoid stitching. Experimental results show that it is a highly-matched and robust video basically achieve real-time stitch. t in matching views. The ghost caused by directly stitch algorithm, and can