Visual Graph Mining

13 Aug 2017Quanshi ZhangXuan SongRyosuke Shibasaki

In this study, we formulate the concept of "mining maximal-size frequent subgraphs" in the challenging domain of visual data (images and videos). In general, visual knowledge can usually be modeled as attributed relational graphs (ARGs) with local attributes representing local parts and pairwise attributes describing the spatial relationship between parts... (read more)

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