The GeoVid project explores the concept of sensor-rich video tagging. Specifically, recorded videos are tagged with a continuous stream of extended geographic properties that relate to the camera scenes. This meta-data is then utilized for storing, indexing and searching large collections of community-generated videos. By considering video related meta-information, more relevant and precisely delimited search results can be returned. Our web site demonstrates a georeferenced video search portal (GVS) that utilizes an estimation model of a camera's viewable scene for effective video search.

To acquire video with the relevant properties, we provide smartphone apps that provide automated annotation of captured videos with their respective field of views (FOV). The acquisition software, available for Android here, allows community-driven data contributions to the search portal. Tagged videos can directly be uploaded from the app. The iPhone app is available from the iTunes App Store here.

Below is a video that explains the ideas and concepts behind GeoVid. Alternatively, you can directly try the georeferenced video search portal (GVS). Please note that the site contains a very small number of videos right now mostly from one location, namely Singapore.

System Requirements: Because of the significant use of JavaScript FOV animations, the video search page works best with the Chrome and Firefox browsers.

People Involved
Roger Zimmermann
Seon Ho Kim
Sakire Arslan Ay
Beomjoo Seo
Jia Hao
Lingyan Zhang
Guanfeng Wang
Shunkai Fang
He Ma