  In this paper, we study a simplified affine motion model based coding
framework to overcome the limitation of translational motion model and maintain
low computational complexity. The proposed framework mainly has three key
contributions. First, we propose to reduce the number of affine motion
parameters from 6 to 4. The proposed four-parameter affine motion model can not
only handle most of the complex motions in natural videos but also save the
bits for two parameters. Second, to efficiently encode the affine motion
parameters, we propose two motion prediction modes, i.e., advanced affine
motion vector prediction combined with a gradient-based fast affine motion
estimation algorithm and affine model merge, where the latter attempts to reuse
the affine motion parameters (instead of the motion vectors) of neighboring
blocks. Third, we propose two fast affine motion compensation algorithms. One
is the one-step sub-pixel interpolation, which reduces the computations of each
interpolation. The other is the interpolation-precision-based adaptive block
size motion compensation, which performs motion compensation at the block level
rather than the pixel level to reduce the interpolation times. Our proposed
techniques have been implemented based on the state-of-the-art high efficiency
video coding standard, and the experimental results show that the proposed
techniques altogether achieve on average 11.1% and 19.3% bits saving for random
access and low delay configurations, respectively, on typical video sequences
that have rich rotation or zooming motions. Meanwhile, the computational
complexity increases of both encoder and decoder are within an acceptable
range.
