固定多摄像头的视频拼接技术  

Video Stitching Technology Based on Fixed Multi-camera

作　　者：刘畅[1] 金立左[1] 费树岷[1] 马军勇 

机构地区：[1]东南大学自动化学院,南京210096 [2]光电控制技术重点实验室,洛阳471009

出　　处：《数据采集与处理》2014年第1期126-133,共8页Journal of Data Acquisition and Processing

基　　金：航空科学基金(20115169016)资助项目;总装预研基金(9140C460302130C46173)资助项目;江苏省自然科学基金(BK20131296)资助项目

摘　　要：视频拼接技术是计算机图形学和计算机视觉的重要分支,它的发展基于静态图像的拼接技术,但由于视频信息的复杂性,视频拼接也有区别于图像拼接,针对实际运用中的实时拼接的需要,本文提出了一种基于控制帧的固定摄像头视频拼接方法。首先采集控制帧图像,对摄像头进行参数标定获得相机内参和光心坐标,再使用一种改进的畸变矫正方法去除摄像头畸变带来的成像失真。然后对控制帧图像进行SIFT特征提取并进行粗匹配,再用RANSAC的方法剔除误匹配点并拟合出图像变换单应阵。最后使用查表法将各摄像头的图像同步投影到大场景图片上,对重合区域进行光亮补偿和多带融合。最终实现速度可达25帧/秒的实时视频拼接。Video stitching is one important branches of computer graphics and computer vision, and it is rooted on the development of static image mosaic technology. However, due to the complexity of the video information, video stitching is different from image mosaic. Aiming at the actual demanding of real-time stitching, a video stitching algorithm of fixed cameras based on control images is proposed. Firstly, the control images are captured in order to calibrate the cameras to get the internal reference and the coordinates of optical center. An improved distor- tion correction algorithm has been applied to deal with the distortion of the cameras so as to control the distortion of the captured control images. The scale invariant feature transform （SIFT） features of the control images are extracted and processed through a rough matching. Then random sample consensus（RANSAC） algorithm is adopted to reduce the number of er- ror-matching and to fit the image homograhy. The method of lookup table is applied to project each image captured from the cameras onto the panorama image. After gain compensation, the overlapped portion is blended by multi-band technique. Finally, the real-time video stitching is implemented, which can reach the final speed of 25 frames per second.

关 键 词：视频拼接 畸变矫正 特征匹配 控制帧 图像融合 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]