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)
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)
Pedestrian detection is one of the most important techniques for surveillance applications. This paper proposes an effective method for pedestrian detection in low-contrast images. The main characteristic of the proposed method is a two-stage moving object extraction. In the first stage, the watershed algorithm is used to extract multiple regions of moving(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)
In order to understand self-organization in helicity-driven systems, we have investigated the dynamics of low-aspect-ratio toroidal plasmas by decreasing the external toroidal field and reversing its sign in time. Consequently, we have discovered that the helicity-driven toroidal plasma relaxes towards the flipped state. Surprisingly, it has been observed(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)
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