Marie Katsurai

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This paper presents a cross-modal approach for extracting semantic relationships of concepts from an image database. First, canonical correlation analysis (CCA) is used to capture the cross-modal correlations between visual features and tag features in the database. Then, in order to measure inter-concept relationships and estimate semantic levels, the(More)
As Internet users increasingly post images to express their daily sentiment and emotions, the analysis of sentiments in user-generated images is of increasing importance for developing several applications. Most conventional methods of image sentiment analysis focus on the design of visual features, and the use of text associated to the images has not been(More)
This paper presents a method for exploring and visualizing tag relationships in photo sharing websites based on distributional representations of tags. First, we find a representative distribution of a tag, which is summarized by the mean and covariance, using features of tagged photos. This distributional representation can jointly consider the semantic(More)
SUMMARY In this paper, a novel framework for extracting visual feature-based keyword relationships from an image database is proposed. From the characteristic that a set of relevant keywords tends to have common visual features, the keyword relationships in a target image database are extracted by using the following two steps. First, the relationship(More)
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