2011 | OriginalPaper | Buchkapitel
Detecting Frequent Patterns in Video Using Partly Locality Sensitive Hashing
verfasst von : Koichi Ogawara, Yasufumi Tanabe, Ryo Kurazume, Tsutomu Hasegawa
Erschienen in: Computer Vision – ACCV 2010 Workshops
Verlag: Springer Berlin Heidelberg
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Frequent patterns in video are useful clues to learn previously unknown events in an unsupervised way. This paper presents a novel method for detecting relatively long variable-length frequent patterns in video efficiently. The major contribution of the paper is that Partly Locality Sensitive Hashing (PLSH) is proposed as a sparse sampling method to detect frequent patterns faster than the conventional method with LSH. The proposed method was evaluated by detecting frequent everyday whole body motions in video.