Event-Based Velocity Prediction for Spiking Neural Networks

This dataset is intended to be used to predict the velocity based on the event pixels present in the data, given in (t, x, y, p) format alongside a ground truth velocity reading. A novel dataset using people and various objects moving in front of an RGB video camera was created. The positions of each entity and the associated times were captured with a Vicon motion tracking system. These two types of data were calibrated so that the movement in the video matched the measurements recorded by the Vicon system. The types of data collected include two different people carrying a calibrated Vicon Active Wand and moving around the room, a Lambda aerial robot with motion tracking markers that flew around the room, a box with motion tracking markers that were tossed back and forth in the air, and the same box was slid across the floor. The video recording was simulated as event camera data. Each pixel changes state independently of all the other pixels. The Open Event Camera Simulator (ESIM) from the Robotics and Perception Group at the University of Zurich and ETH Zurich is used. The event camera simulator used, ESIM, allows for accurate event simulation data. The ground truth velocities were calculated from the position and timestamps recorded by the Vicon system.