We are studying about automatic production of soccer sports videos for easy understanding by using digital camera work on camera fixed videos. The digital camera work is a movie technique which uses virtual panning and zooming by clipping frames from hi-resolution images and controlling the frame size and position. We have studied so far digital panning. In this paper, we propose a method of digital zooming by automatically recognizing the game situation or events such as penalty kick and free kick based on player and ball tracking. These recognition results are used as key indices to retrieve the event scenes from soccer videos. We compared the proposed technique with a conventional technique by AHP method that can reflect an individual subjectivity.
This paper proposes a method to automatically extract highlight scenes from sports (baseball) live video in real time and to allow users to retrieve them. For this purpose, sophisticated speech recognition is employed to convert the speech signal into the text and to extract a group of keywords in real time. Image processing detects, also in real time, the pitcher scenes and extracts pitching sections starting from a pitcher scene and ending at the successive pitcher scene. Highlight scenes are extracted as the pitching sections with the keywords such as home run, two-base hit and three-base hit extracted from speech signals.
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