Kazuhiko Murasaki

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Estimating the nutritional value of food based on image recognition is important to health support services employing mobile devices. The estimation accuracy can be improved by recognizing regions of food objects and ingredients contained in those regions. In this paper, we propose a method that estimates nutritional information based on segmentation and(More)
This paper proposes a novel method of discovering a set of image <i>contents</i> sharing a specific <i>context</i> (attributes or implicit meaning) with the help of image collections obtained from social curation platforms. Socially curated contents are promising to analyze various kinds of multimedia information, since they are manually filtered and(More)
How can a machine learn to recognize visual attributes emerging out of online community without a definitive supervised dataset? This paper proposes an automatic approach to discover and analyze visual attributes from a noisy collection of image-text data on the Web. Our approach is based on the relationship between attributes and neural activations in the(More)
In this paper, we propose a robust and real-time 3D human shape reconstruction method in daily life spaces to make practical voxel-based motion capture systems. Our algorithm extracts human silhouette and reconstructs human shape via volume intersection from multi view point images. The method presented in this paper is based on energy minimization via(More)
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