一种移动视频与地理场景的融合方法

快速准确地了解灾害现场状况是救灾过程中的重中之重。通常发生灾害都会使用无人机进行现场勘察，但是无人机视频难以与实际的地理场景关联起来，为此本文提出了一种移动视频与地理场景的融合方法。该方法首先采用具有仿射不变性的ASIFT算法检测特征点，将匹配后的特征点采用RANSAC算法进行迭代剔除噪点，计算视频与地理场景最优的透视变换矩阵模型参数；然后将计算得到的透视变换参数应用到视频数据，恢复视频角点坐标；最后通过内插得出所有视频帧的角点坐标，实现视频与DOM的精确融合。试验结果表明，对视频数据匹配的间隔帧越短，其整体融合精度越高，通过本文方法进行视频与地理场景融合的误差标准差低于10 m。

A fusion method of mobile video and geographic scene

Quick and accurate understanding of the disaster scene situation is the top priority in the disaster relief process. Usually, drones are used for site surveys when disasters occur, but it is difficult to associate the drone video with the actual geographic scene. To this end, this paper proposes a fusion method of mobile video and geographic scene. This method first uses ASift algorithm with affine invariance to detect feature points, and uses the RANSAC algorithm to iteratively remove noise points to calculate video and geography, optimal scene transformation matrix model parameters. Then the calculated perspective transformation parameters are then applied to the video data to restore the coordinates of the corners of the video. Finally, the corner coordinates of all video frames are obtained by interpolation to achieve an accurate fusion of video and DOM. The experimental results show that the shorter the interval frame that matches the video data, the higher the overall fusion accuracy, the standard deviation of the video and geographic scene fusion by this method is less than 10 m.