GeoUGV: User-Generated Mobile Video Dataset with Fine Granularity Spatial Metadata

Author: University of Southern California

Partner: No

Contact: Ying Lu (ylu720@usc.edu) Hien To(hto@usc.edu) Abdullah Alfarrarjeh (alfarrar@usc.edu) Seon Ho Kim (seonkim, shahabi@usc.edu) Yifang Yin (yifang@comp.nus.edu.sg) Roger Zimmermann (rogerz@comp.nus.edu.sg) Cyrus Shahabi (shahabi@usc.edu)

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Ratings: 289

Description

When analyzing and processing videos, it has become increasingly important in many applications to also consider contextual information, in addition to the content. With the ubiquity of sensor-rich smartphones, acquiring a continuous stream of geo-spatial metadata that includes the location and orientation of a camera together with the video frames has become practical. However, no such detailed dataset is publicly available. In this paper we present an extensive geo-tagged video dataset named GeoUGV that has been collected as part of the MediaQ and GeoVid projects. The key features of the dataset are that each video file is accompanied by a metadata sequence of geo-tags consisting of GPS locations, compass directions, and spatial keywords at fine-grained intervals. The GeoUGV dataset has been collected by volunteer users and its statistics can be summarized as follows: 2,397 videos containing 208,976 video frames that are geo-tagged, collected by 289 users in more than 20 cities across the world over a period of 10 years (2007–2016). We hope that this dataset will be useful for researchers, scientists and practitioners alike in their work.

Access

The files are available for download via HTTP. Link: http://geovid.org/dataset/

References and Citation

Use of the datasets in published work should be acknowledged by a full citation to the authors’ papers [LTA16] at the MMSys conference: Proceedings of ACM MMSys’16, Klagenfurt am Wörthersee, Austria, May 10-13, 2016.

References

  • LTA16: Lu, Y., To, H., Alfarrarjeh, A., Kim, S.H., Yin, Y., Zimmermann, R., Shahabi, C. GeoUGV: User-generated mobile video dataset with fine granularity spatial metadata, Proceedings of the 7th International Conference on Multimedia Systems, MMSys 2016, pp. 338-343.