Design and implementation of geo-tagged video search framework

User generated video content is experiencing significant growth which is expected to continue and further accelerate. As an example, users are currently uploading 20 h of video per minute to YouTube. Making such video archives effectively searchable is one of the most critical challenges of multimedia management. Current search techniques that utilize signal-level content extraction from video struggle to scale.Here we present a framework based on the complementary idea of acquiring sensor streams automatically in conjunction with video content. Of special interest are geographic properties of mobile videos. The meta-data from sensors can be used to model the coverage area of scenes as spatial objects such that videos can effectively, and on a large scale, be organized, indexed and searched based on their field-of-views. We present an overall framework that is augmented with our design and implementation ideas to illustrate the feasibility of this concept of managing geo-tagged video.