映像情報メディア学会誌
Online ISSN : 1881-6908
Print ISSN : 1342-6907
ISSN-L : 1342-6907
特集論文
行列演算に基づく高速かつ厳密な大規模映像データ処理
白浜 公章上原 邦昭
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ジャーナル フリー

2013 年 67 巻 7 号 p. J241-J251

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There are two important issues for accurate concept detection in videos. One is to train a concept detector with a large number of training examples. The other is to extract the feature representation of a shot based on descriptors, which are densely sampled in both the spatial and temporal dimensions. This paper describes two fast and exact methods based on matrix operation, where a large amount of data are processed in a batch without any approximation. The first method trains a concept detector based on batch computation of similarities among many training examples. The second method extracts the feature representation of a shot by computing probability densities of many descriptors in a batch. The experimental results validate the efficiency and effectiveness of our methods. In particular, the concept detection result obtained by our methods was ranked top in the annual worldwide competition, TRECVID 2012 Semantic Indexing (light).

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© 2013 一般社団法人 映像情報メディア学会
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