  Surveying wide areas with only one camera is a typical scenario in
surveillance and automotive applications. Ultra wide-angle fisheye cameras
employed to that end produce video data with characteristics that differ
significantly from conventional rectilinear imagery as obtained by perspective
pinhole cameras. Those characteristics are not considered in typical image and
video processing algorithms such as motion estimation, where translation is
assumed to be the predominant kind of motion. This contribution introduces an
adapted technique for use in block-based motion estimation that takes into the
account the projection function of fisheye cameras and thus compensates for the
non-perspective properties of fisheye videos. By including suitable
projections, the translational motion model that would otherwise only hold for
perspective material is exploited, leading to improved motion estimation
results without altering the source material. In addition, we discuss
extensions that allow for a better prediction of the peripheral image areas,
where motion estimation falters due to spatial constraints, and further include
calibration information to account for lens properties deviating from the
theoretical function. Simulations and experiments are conducted on synthetic as
well as real-world fisheye video sequences that are part of a data set created
in the context of this paper. Average synthetic and real-world gains of 1.45
and 1.51 dB in luminance PSNR are achieved compared against conventional block
matching. Furthermore, the proposed fisheye motion estimation method is
successfully applied to motion compensated temporal resolution enhancement,
where average gains amount to 0.79 and 0.76 dB.
