GeoUGV: user-generated mobile video dataset with fine granularity spatial metadata

Ying Lu, Hien To, Abdullah Alfarrarjeh, Seon Ho Kim, Yifang Yin, Roger Zimmermann, Cyrus Shahabi

Abstract: 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 [3] and GeoVid [1] 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.