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A new event camera dataset, EVIMO2, is introduced that improves on thepopular EVIMO dataset by providing more data, from better cameras, in morecomplex scenarios. As with its predecessor, EVIMO2 provides labels in the formof per-pixel ground truth depth and segmentation as well as camera and objectposes. All sequences use data from physical cameras and many sequences featuremultiple independently moving objects. Typically, such labeled data isunavailable in physical event camera datasets. Thus, EVIMO2 will serve as achallenging benchmark for existing algorithms and rich training set for thedevelopment of new algorithms. In particular, EVIMO2 is suited for supportingresearch in motion and object segmentation, optical flow, structure frommotion, and visual (inertial) odometry in both monocular or stereoconfigurations.  EVIMO2 consists of 41 minutes of data from three 640$\times$480 eventcameras, one 2080$\times$1552 classical color camera, inertial measurementsfrom two six axis inertial measurement units, and millimeter accurate objectposes from a Vicon motion capture system. The dataset's 173 sequences arearranged into three categories. 3.75 minutes of independently moving householdobjects, 22.55 minutes of static scenes, and 14.85 minutes of basic motions inshallow scenes. Some sequences were recorded in low-light conditions whereconventional cameras fail. Depth and segmentation are provided at 60 Hz for theevent cameras and 30 Hz for the classical camera. The masks can be regeneratedusing open-source code up to rates as high as 200 Hz.  This technical report briefly describes EVIMO2. The full documentation isavailable online. Videos of individual sequences can be sampled on the downloadpage.

EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow,  Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with  Monocular or Stereo Algorithms