  To watch 360{\deg} videos on normal 2D displays, we need to project the
selected part of the 360{\deg} image onto the 2D display plane. In this paper,
we propose a fully-automated framework for generating content-aware 2D
normal-view perspective videos from 360{\deg} videos. Especially, we focus on
the projection step preserving important image contents and reducing image
distortion. Basically, our projection method is based on Pannini projection
model. At first, the salient contents such as linear structures and salient
regions in the image are preserved by optimizing the single Panini projection
model. Then, the multiple Panini projection models at salient regions are
interpolated to suppress image distortion globally. Finally, the temporal
consistency for image projection is enforced for producing temporally stable
normal-view videos. Our proposed projection method does not require any
user-interaction and is much faster than previous content-preserving methods.
It can be applied to not only images but also videos taking the temporal
consistency of projection into account. Experiments on various 360{\deg} videos
show the superiority of the proposed projection method quantitatively and
qualitatively.
