  When dynamic objects are captured by a camera, motion blur inevitably occurs.
Such a blur is sometimes considered as just a noise, however, it sometimes
gives an important effect to add dynamism in the scene for photographs or
videos. Unlike the similar effects, such as defocus blur, which is now easily
controlled even by smartphones, motion blur is still uncontrollable and makes
undesired effects on photographs. In this paper, an unified framework to add
motion blur on per-object basis is proposed. In the method, multiple frames are
captured without motion blur and they are accumulated to create motion blur on
target objects. To capture images without motion blur, shutter speed must be
short, however, it makes captured images dark, and thus, a sensor gain should
be increased to compensate it. Since a sensor gain causes a severe noise on
image, we propose a color compensation algorithm based on non-linear filtering
technique for solution. Another contribution is that our technique can be used
to make HDR images for fast moving objects by using multi-exposure images. In
the experiments, effectiveness of the method is confirmed by ablation study
using several data sets.
