A Synchronized Stereo and Plenoptic Visual Odometry Dataset
This dataset addresses the need for standardized evaluation in visual odometry research, particularly for emerging plenoptic camera methods, though it is incremental as it builds on existing dataset creation practices.
The authors introduced a synchronized dataset for evaluating visual odometry algorithms using monocular, stereo, and plenoptic cameras, recorded in challenging indoor and outdoor scenarios with 11 sequences to measure tracking accuracy via drift in looped scenes.
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.