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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Visual-inertial input datasets for SLAM applications containing extreme and human-like motion patterns

Authors: Czentye, János;

Visual-inertial input datasets for SLAM applications containing extreme and human-like motion patterns

Abstract

Recorded datasets in compressed rosbag format, which contain visual and IMU sensor information that are bearing high resemblance to the movement of a human player with a handheld AR-capable device. For machine learning training and validation tasks, separate dataset are available containing motion patterns in a wide range from steady camera image to extremely challenging movements.

{"references": ["J. Czentye, B. P. Ger\u0151 and B. Sonkoly, \"Managing Localization Delay for Cloud-assisted AR Applications Via LSTM-driven Overload Control,\" 2021 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), 2021, pp. 92-101, doi: 10.1109/AIVR52153.2021.00023."]}

Keywords

SLAM, Visual-Inertial SLAM, ROS, IMU, Extreme Motion, AR game

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