Robust detection of stylized text events in digital video

Automatic content-based video indexing is an important research problem. One approach is to extract text appearing in video as an indication of a scene´s semantic content. Most work so far has focused only on detecting the spatial extent of text instances in individual video frames. But text occurring in video usually persists for several seconds. This constitutes a text event that should be entered only once in the video index. Therefore it is necessary to determine the temporal extent of text events by combining the results of text detection on individual frames, over time. This is a nontrivial problem because a text event may move, rotate, grow, shrink, or otherwise change throughout its lifetime. Such text effects are common in television programs and commercials to attract viewer attention, but have so far been ignored in the literature. We present a method for detecting and tracking moving, changing caption text events in MPEG-1 compressed video