In video surveillance as well as automotive applications, so-called fisheye
cameras are often employed to capture a very wide angle of view. As such
cameras depend on projections quite different from the classical perspective
projection, the resulting fisheye image and video data correspondingly exhibits
non-rectilinear image characteristics. Typical image and video processing
algorithms, however, are not designed for these fisheye characteristics. To be
able to develop and evaluate algorithms specifically adapted to fisheye images
and videos, a corresponding test data set is therefore introduced in this
paper. The first of those sequences were generated during the authors' own work
on motion estimation for fish-eye videos and further sequences have gradually
been added to create a more extensive collection. The data set now comprises
synthetically generated fisheye sequences, ranging from simple patterns to more
complex scenes, as well as fisheye video sequences captured with an actual
fisheye camera. For the synthetic sequences, exact information on the lens
employed is available, thus facilitating both verification and evaluation of
any adapted algorithms. For the real-world sequences, we provide calibration
data as well as the settings used during acquisition. The sequences are freely
available via www.lms.lnt.de/fisheyedataset/.

本文介绍了一个包含了合成和真实鱼眼图像以及相应的校准数据和测试设置的数据集，以便能够开发和评估适用于鱼眼图像和视频的专门算法。