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Machine vision
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IEEE Transactions on Image Processing
Stratification Approach to Modeling Video
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Motion Activity Based Shot Identification and Closed Caption Detection for Video Structuring
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Face tracking in the compressed domain
EURASIP Journal on Applied Signal Processing
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Multimedia Tools and Applications
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
Knowledge-discounted event detection in sports video
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on model-based diagnostics
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CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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In this paper, we propose a new method for detecting text captions in MPEG video stream. It is based on the observation that text captions in video frames typically possess high contrast against the background for them to be visible. The method operates on DCT coefficients in MPEG domain. The main contribution of this work is in developing a binarzied contrast feature domain in which the presence of text in video frames can be highlighted. A weighting function is defined to deduce the probability of a text frame. From the set of representative text frames located, further techniques are developed to outline, segment, and recognise text captions. The techniques have been tested on commercial and news videos from the MPEG7 data set and local TCS news video. The results demonstrate that our approach is effective in detecting and locating text captions in general video.