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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
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Headcam: Cylindrical Panoramic Video Dataset for Unsupervised Learning of Depth and Ego-Motion

Authors: Alisha Sharma; Jonathan Ventura;

Headcam: Cylindrical Panoramic Video Dataset for Unsupervised Learning of Depth and Ego-Motion

Abstract

This dataset contains panoramic video captured from a helmet-mounted camera while riding a bike through suburban Northern Virginia. We used the videos to evaluate an unsupervised learning method for depth and ego-motion estimation, as described in our paper: Alisha Sharma and Jonathan Ventura. "Unsupervised Learning of Depth and Ego-Motion from Cylindrical Panoramic Video." Proceedings of the 2019 IEEE Artificial Intelligence & Virtual Reality Conference, San Diego, CA, 2019. If you make use of this dataset, please cite this paper. The videos are stored as .mkv video files encoded using lossless H.264. To extract the images, we recommend using ffmpeg: mkdir 2018-10-03 ; ffmpeg -i 2018-10-03.mkv -q:v 1 2018-10-03/%05d.png ; Associated code can be found in our GitHub repository.

This material is based upon work supported by the National Science Foundation under Grant Nos. 1659788 and 1464420. This work was performed as part of an REU program at the University of Colorado Colorado Springs.

Keywords

panorama, video, unsupervised learning, computer vision

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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