ゼミナール講演

日時: 平成24年12月11日(火)2限 (11:00 -- 12:30) 通常のゼミの時間とは異なります
場所: L1

講演者: 浦西 友樹(大阪大学)
題目: Activity Report of Overseas Visit: Supporting Daily Life of Senior Citizens with a Range Image Sensor, a Camera and a Projector
概要: QoL of senior citizens who intend to live independently should be maintained and supported properly. A laboratory which I have been is focusing on supporting kitchen work of senior citizens, and I have proposed two methods for supporting daily life of senior citizens during the visit. One is Re-PITASu (Rangeimage-Projector Interaction Tool for Arbitrary Surfaces), and the other is grid-based work indication method by using a range image sensor, a camera and a projector. A common technical issue is a calibration between devices used in the proposed methods, because it is particularly difficult to calibrate between the range image sensor and other devices. I have introduced indirect calibration framework to calibrate between the devices. A prototype and a demonstration of the proposed methods are shown in this seminar.

講演者: 垣内 正年
題目: Activity report at INRIA Paris-Rocquencourt: open source implementation of GeoNetworking based on ITS station architecture
概要: Cooperative ITS is a new vision of Intelligent Transportation Systems (ITS) where vehicles, the road side infrastructure, traffic control centers, road users, road authorities, road operators, etc. exchange and share information based on a common communication architecture known as the ITS station reference architecture. To promote the deployment of Cooperative ITS and to encourage further research on it, I developed an open-source software combining IPv6 and GeoNetworking which are two essential building blocks of the ITS station. This research has performed in IMARA project at INRIA Paris-Rocquencourt under the strategic young researcher overseas visits program for accelerating brain circulation supported by JSPS.

講演者: 粂 秀行
題目: Topometric Localization for Autonomous Vehicle
概要: Applications of autonomous vehicle, for example parking and commuting, usually take the same route each time. In this talk, we will propose a method to localize a vehicle along a previously driven route by using images. In the method, first, we estimate rough position by using Topometric Localization which identifies the most similar image from the previously captured images by considering topological and metric information. Next, precise position and posture are estimated from 3D positions of feature points which have been reconstructed beforehand.

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