Semantic retrieval in a large-scale video database by using both image and text feature

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Abstract

The paper demonstrates a new retrieval method of intergrating both image features and text informations derived from video data. We compare not only image similiarity, also narrow the retrieval sets in advance by employing searching in text keywords. Users inputs also performs the key role in improving retrieval accuracy. © Springer-Verlag Berlin Heidelberg 2004.

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Yu, C., Mo, H., Katayama, N., Satoh, S., & Asano, S. (2004). Semantic retrieval in a large-scale video database by using both image and text feature. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3332, 770–777. https://doi.org/10.1007/978-3-540-30542-2_95

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