This service detects fragments of interests (called HotSpots) within online videos and enables their exploration.
The approach combines visual analysis techniques and background knowledge from the web of data in order to quickly get an overview about the video content and therefore promote media consumption at the fragment level. First, we perform a chapter segmentation by combining visual features and semantic units (paragraphs) available in transcripts. Second, we semantically annotate those segments via Named Entity Extraction and topic detection. We then identify consecutive segments talking about similar topics and entities that we merge into bigger and semantic independent media units. Finally, we rank those segments and filter out the lowest scored candidates, in order to propose a summary that illustrates the HotSpots in a dedicated media fragment player.
An online demo is available at http://linkedtv.eurecom.fr/mediafragmentplayer.