Content-based Online News Query [CONQuer] using scene change detection and recognized speech - Del Rosario, Alwin B. (2006)
The onset of the information age brought with it the technology advances that enable faster and more efficient ways to transfer information across geographic boundaries, allowing the delivery of an increasing diversity of digital multimedia to an ever-expanding audience. News, for example, has proliferated from the airwaves to the wires, accompanied by an influx of information, resulting in an explosion both in content and demand. Ironically, people are also finding less time to absorb the huge amount of information available, so there is a need to give them the freedom to choose only the news they feel is relevant. This is where CONQuer comes into play. "CONQuer" stands for Content-based Online News Query. It hopes to rise to the challenges by providing its users a means by which they can choose only the news they want. The CONQuer system is a news video clip search that includes semantics in addition to the filenames when searching through a collection of video files. To achieve this, CONQuer divides the files in its database into logical video segments with the use of 2 scene-change detection techniques based on the video and audio streams, respectively: optimized color histogram difference threshold and detection of low energy signals. Speech recognition is then used to extract textual information from each clip's audio stream. A mapping between text and video clips is then established, which would then be used by the search module to retrieve results based on a user-supplied text query.