The growing amount of video data has raised the need for automatic semantic information indexing and retrieval systems. To accomplish to these needs, the text information in images and videos is proved to be an important source of high-level semantics. This paper discusses the video OCR system designed for overlay text based automatic indexing and retrieval in the video streams. The proposed framework consists of the video segmentation, the video key-frame extraction, the video text recognition, and the entity detection. The experimental results on Korean television news programs show that the proposed method efficiently realizes the automatic indexing in the video streams.
CITATION STYLE
Lee, S., & Jo, K. (2018). Entity Detection for Information Retrieval in Video Streams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10956 LNAI, pp. 618–627). Springer Verlag. https://doi.org/10.1007/978-3-319-95957-3_64
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