In this work we present an approach for video content representation based on the detection of recurring visual elements or regions. We hypothesize that such elements play a potentially central role in the underlying video sequence. The approach makes use of fundamental intrinsic properties of a video and, thus, it does not make any assumptions about the video content itself. Furthermore, our approach does not require for any training or prior knowledge about the general settings and video domain. Preliminary experiments with a small and heterogeneous dataset of web videos demonstrate the potential of the approach to be employed as a compact summary of the video content with focus on its central visual elements. Additionally, resulting representations enable the retrieval of video sequences sharing common visual elements.
L. Diem, M. Zaharieva: "Video Content Representation Using Recurring Regions Detection"; Talk: International Conference on MultiMedia Modeling, Miami, FL, USA; 01-04-2016 - 01-06-2016; in: "MultiMedia Modeling", (2016), ISBN: 978-3-319-27670-0; 6 pages.
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