| Budget Amount *help |
¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2012: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Outline of Final Research Achievements |
We studied learning machine using the generative models and simple discriminator. We proposed a new framework of Markov random field that has kernelalized potential function. We showed an efficient method of computation and that this model generates essentially linearly separable kernel features if the degree of kernel is large.
We conducted experiments on the face detection using the appearance based approach, and showed that our method can attain comparable results with the state-of-the-art face detection methods based on AdaBoost, SURF, and cascade despite of smaller data size and no preprocessing.
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