Text detection, localization, and tracking in compressed video
Image Communication
A model-based iterative method for caption extraction in compressed MPEG video
SAMT'07 Proceedings of the semantic and digital media technologies 2nd international conference on Semantic Multimedia
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Videotext extraction is a core technique for multimedia applications such as News-On-Demand (NOD) and digital libraries, and research about videotext extraction have been conducted vigorously. In this paper, we propose an efficient method for extracting texts in MPEG compressed videos for content-based indexing. The proposed method makes the best use of 2-level DCT coefficients and macroblock type information in MPEG compressed video, and this method can be organized into three stages to increase overall performance: text frame detection, text region extraction, and character extraction. The main advantage of the proposed method is that it can avoid the overhead of decompressing video into individual frames in the pixel domain. We evaluated this method using various types of news video data.