A Comparative Study of Algorithms for Realtime Panoramic Video Blending

Unlike image blending algorithms, video blending algorithms have been little studied. In this paper, we investigate six popular blending algorithms-feather blending, multi-band blending, modified Poisson blending, mean value coordinate blending, multi-spline blending, and convolution pyramid blending. We consider their application to blending realtime panoramic videos, a key problem in various virtual reality tasks. To evaluate the performances and suitabilities of the six algorithms for this problem, we have created a video benchmark with several videos captured under various conditions. We analyze the time and memory needed by the above six algorithms, for both CPU and GPU implementations (where readily parallelizable). The visual quality provided by these algorithms is also evaluated both objectively and subjectively. The video benchmark and algorithm implementations are publicly available.