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Dear colleagues, We are very happy to announce the release of the first public collection of datasets recorded with an event camera (DAVIS) for pose estimation, visual odometry, and SLAM applications! The data also include intensity images, inertial measurements, ground truth from a motion-capture system, synthetic data, as well as an event camera simulator that allows you to create your own sequences! All the data are released both as standard text files and binary files (i.e., rosbag). Dataset: http://rpg.ifi.uzh.ch/davis_data.html We provide data: About event cameras and the DAVIS sensor Event cameras are revolutionary vision sensors that overcome the limitations of standard cameras in scenes characterized by high-dynamic range and high-speed motion: https://youtu.be/iZZ77F-hwzs However, as these cameras are still expensive and not widely spread, we hope that will accelerate research on event-based algorithms! We greatly acknowledge our sponsors: the DARPA FLA Program, the Google Faculty Research Award, the Qualcomm Innovation Fellowship, the SNSF-ERC Starting Grant, NCCR Robotics, the Swiss National Science Foundation, and the UZH Forschungskredit. All feedback is very welcome! Elias Mueggler, Henri Rebecq, Guillermo Gallego, Tobi Delbruck, Davide Scaramuzza |
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