Summarization from Multiple User Generated Videos in Geo-Space

Abstract

In recent years, we have witnessed an overwhelming number of user-generated videos being captured on a daily basis. The problem of an efficient summarization from multiple videos is emerged consequently. In this thesis, we investigate how to formulate, display and improve a multi-video summarization with the following contributions. The first three works propose solutions to detect region of interests among multiple videos according to their geographic properties and convert the summarization to a graph-analysis problem with a dynamic programming-based solution to achieve the optimized informativeness, quality and coherency. The fourth work proposes an interactive and dynamic video exploration system where people can conduct personalized summary queries through direct map-based manipulations. Lastly, we investigate whether external crowdsourcing databases contribute to improving the summary quality by recommending a list of photography spots which are of potential to capture appealing photos for a landmark.