****Arcturus Industries, LLC (”Arcturus Industries”), and its affiliates strive to promote future development in the field of VR tracking. Using their equipment, Arcturus Industries collected, annotated, transformed, synthesized and organized IMU and other tracking data in a dataset (the “DIPr Dataset”). By using or downloading the “DIPr Dataset”, you are agreeing to comply with the terms of this page and any licensing terms referenced below.
”DIPr Dataset”, code, and any associated data or documentation are provided free of charge under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License (“CC BY-NC-SA 4.0”). The full text of the license is accessible at **https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.**
We license “DIPr Dataset” data and documents for non-commercial use only. Under the terms of the CC BY-NC-SA 4.0 “non-commercial” means “not primarily intended for or directed towards commercial advantage or monetary compensation.” To assist you in determining whether your contemplated use is non-commercial, we make available the following examples:
You are a researcher at an academic institution, working on computer vision and prediction. You use “DIPr Dataset” dataset to further advance your research and publish results based on the “DIPr Dataset” benchmark. Your published paper includes imagery and figures derived from the “DIPr Dataset” dataset. The imagery and figures are attributed to “DIPr Dataset” and a hyperlink to the text of the CC-BY-NC-SA 4.0 license is provided.
You are a researcher at a virtual reality hardware company. You are submitting your IMU-based pose estimation algorithm to a major conference for public review. You use the “DIPr Dataset” dataset to train and evaluate your method. You publish the results of the comparison publicly. The “DIPr Dataset” data in your paper is attributed in accordance with the CC-BY-NC-SA 4.0 license.
You are an engineer at virtual reality hardware company. You use the “DIPr Dataset” dataset to train a prototype of IMU tracking fallback algorithm. You use this prototype detection model as a placeholder until you build a large enough internal dataset to train your model against.
You are an engineer at a company that produces a robotics platform for sale. You train the prediction machine learning model in your company’s product on data from the “DIPr Dataset” dataset. Your company releases the product for sale with the model you trained against “DIPr Dataset” data.
If you use “DIPr Dataset” and identify areas that could benefit from changes, we would like to hear from you. Please submit any comments on the issues page of our GitHub repository. If you submit your changes, you may be required to confirm that your changes are subject to CC BY-NC-SA 4.0.
Please follow the attribution guidelines provided in section 3.A. of CC-BY-NC-SA 4.0 license with the copyright notice being “© 2021-2022 Arcturus Industries, LLC”.
You may not use the Arcturus Industries’ trademark, logo, or name without Arcturus Industries express written permission in connection with “DIPr Dataset”.