文件名称:Aspatial-temporalapproachforvideocaptiondate
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We present a video caption detection and recognition
system based on a fuzzy-clustering neural network (FCNN) classifier.
Using a novel caption-transition detection scheme we locate
both spatial and temporal positions of video captions with high precision
and efficiency. Then employing several new character segmentation
and binarization techniques, we improve the Chinese
video-caption recognition accuracy from 13 to 86 on a set of
news video captions. As the first attempt on Chinese video-caption
recognition, our experiment results are very encouraging.-A spatial-temporal approach for video caption date
system based on a fuzzy-clustering neural network (FCNN) classifier.
Using a novel caption-transition detection scheme we locate
both spatial and temporal positions of video captions with high precision
and efficiency. Then employing several new character segmentation
and binarization techniques, we improve the Chinese
video-caption recognition accuracy from 13 to 86 on a set of
news video captions. As the first attempt on Chinese video-caption
recognition, our experiment results are very encouraging.-A spatial-temporal approach for video caption date
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A spatial-temporal approach for video caption date.pdf