| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Outline of Final Research Achievements |
Image segmentation is a process to divde a given image into segments corresponding to objects or some meaningful areas. We have developed a new image segmentation algorithm which uses Gaussian processes (GPs), and it accomplished significant improvements in segmentation accuracy. GPs are used to model spatial correlations in images. Although existing methods uses Markov Random Fields (MRFs) for the purpose, GPs have some advantages over MRFs. For example, GPs can specify spatial correlations more directly and more flexibly than MRFs can. Moreover, GPs can model spatial correlations independently of
image resolution.
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