Detecting frequent patterns in video using partly locality sensitive hashing

Authors:
Koichi Ogawara;Yasufumi Tanabe;Ryo Kurazume;Tsutomu Hasegawa
Affiliations:
Kyushu University;Kyushu University;Kyushu University;Kyushu University
Venue:
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Year:
2010

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Abstract

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.