Real-time video stitching

This paper presents a real-time video stitching system which can stitch videos acquired from multiple moving cameras. Most conventional stitching methods were developed under the assumption of static scenes without considering moving objects. However, cameras could move freely for general video stitching and the homography matrices between different camera views could vary from frame to frame. The proposed algorithm estimates the refined homography in both spatial and temporal domains. To be more specific, we first estimate homography between images acquired by different cameras by using RANSAC in the spatial domain at some key frames separated by a fixed interval. Then, we obtain temporally smooth homography transformations by using temporally linear interpolation for the frames between the key frames. For the image stitching, we correct the exposure of the stitched image by linear blending in the overlapping region and generate a panoramic view with cylindrical warping. To achieve real-time video stitching, we speed up our system with CUDA parallel programming. The experimental results show that the stitched views by using the proposed algorithm compare favorably with other methods. In addition, our video stitching system can achieve real-time performance and it is much more efficient compared to the other methods included in our experimental comparison.