Abstract

For companies, TV commercial is a very important way to introduce and advertise their products. It is expensive to put an advertisement on TV. So these companies generally charge other companies to monitor that their TV commercials are broadcasted properly as contracted. Currently, these monitorings have been done manually. The monitoring company records all the TV programs and their air-times while they are being broadcasted. Then the agent checks the starting-times and the ending-times of TV commercials. Video retrieval and matching techniques can be used to monitor TV commercials automatically. By extracting visual features that can identify commercials, we can measure similarities and identify a target video from thousands of videos. To process all the TV programs of 24 hours a day, feature extraction and matching process must be done in real-time. In this paper, we designed the visual feature DB for real-time processing and implemented real-time TV commercial monitoring system. To construct the DB, we extracted scene change information, block-based dominant colors and edge pattern histograms of TV commercial clips.KeywordsDominant ColorScene ChangeVideo FeatureEdge PatternQuery VideoThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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