Keiji Gyohten

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Detecting humans in an image sequence is one of the most difficult problems in object recognition. It is necessary to define a robust descriptor which can extract human features from images, to improve the detecting performance. Histograms of Oriented Gradients(HOG) descriptor significantly outperforms compared with the others on human detection. The(More)
This paper presents a method which reduces uncertainty of a position and a direction of an autonomous robot by observing environment with a camera. In the proposed method, the state of the robot is represented by a state vector obeying a probability distribution. The robot creates and renews an environment map by considering the information from the mounted(More)
In this research, we propose CAD data mining technique to obtain semantic elements without prior knowledge about plans being designed. Our method consists of two steps. The first step is to extract frequent spatial relations between figure elements in CAD data as clues to the semantic elements. These relations are modeled as topology graph and are analyzed(More)
In this paper, we propose a system which decides a camera work in 3D virtual space and generates 3DCG animation automatically. The system is called "Data Animating." The system generates 3DCG animation according to user's select of soccer's play event. The 3D virtual space is composed of player position and play event data estimated from soccer footage. We(More)
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