  We present a new dataset to evaluate monocular, stereo, and plenoptic camera
based visual odometry algorithms. The dataset comprises a set of synchronized
image sequences recorded by a micro lens array (MLA) based plenoptic camera and
a stereo camera system. For this, the stereo cameras and the plenoptic camera
were assembled on a common hand-held platform. All sequences are recorded in a
very large loop, where beginning and end show the same scene. Therefore, the
tracking accuracy of a visual odometry algorithm can be measured from the drift
between beginning and end of the sequence. For both, the plenoptic camera and
the stereo system, we supply full intrinsic camera models, as well as
vignetting data. The dataset consists of 11 sequences which were recorded in
challenging indoor and outdoor scenarios. We present, by way of example, the
results achieved by state-of-the-art algorithms.
