  Unlike image blending algorithms, video blending algorithms have been little
studied. In this paper, we investigate 6 popular blending algorithms---feather
blending, multi-band blending, modified Poisson blending, mean value coordinate
blending, multi-spline blending and convolution pyramid blending. We consider
in particular realtime panoramic video blending, a key problem in various
virtual reality tasks. To evaluate the performance of the 6 algorithms on this
problem, we have created a video benchmark of several videos captured under
various conditions. We analyze the time and memory needed by the above 6
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.
