| Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Outline of Final Research Achievements |
In this project, we have presented distributed active sensing methods for a visual sensor network, a networked multi-camera system, so as to maximize the acquired information on environment. We first have developed two different active sensing methodologies based on game theoretic learning theory, which do never require prior knowledge on uncertain environment. We then have presented another approach using distributed optimization on matrix manifolds in order to accelerate adaptability to environmental changes. In addition, a novel distributed target motion prediction algorithm has been proposed in the project. Moreover, we have built a testbed of the visual sensor network system and then have demonstrated all of the above algorithms. Also, a novel simulator of the sensor network system has been developed using a 3D animation software, called blender.
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