  It is hard to estimate optical flow given a realworld video sequence with
camera shake and other motion blur. In this paper, we first investigate the
blur parameterization for video footage using near linear motion elements. we
then combine a commercial 3D pose sensor with an RGB camera, in order to film
video footage of interest together with the camera motion. We illustrates that
this additional camera motion/trajectory channel can be embedded into a hybrid
framework by interleaving an iterative blind deconvolution and warping based
optical flow scheme. Our method yields improved accuracy within three other
state-of-the-art baselines given our proposed ground truth blurry sequences;
and several other realworld sequences filmed by our imaging system.
