Grant-in-Aid for Scientific Research (B)
|Allocation Type||Single-year Grants |
|Research Institution||Nara Institute of Science and Technology |
YOKOYA Naokazu Graduate School of Information Science, Nara Institute of Science and Technology, Professor, 情報科学研究科, 教授 (10252834)
YAMAZAWA Kazumasa Graduate School of Information Science, Nara Institute of Science and Technology, Research Associate, 情報科学研究科, 助手 (40283931)
IWASA Hidehiko Graduate School of Information Science, Nara Institute of Science and Technology, Research Associate, 情報科学研究科, 助手 (50263447)
TAKEMURA Haruo Graduate School of Information Science, Nara Institute of Science and Technology, Associate Professor, 情報科学研究科, 助教授 (60263430)
KIYOKAWA Kiyoshi Communications Research Laboratory, Nara Institute of Science and Technology, Researcher, 通信システム部, 研究員
|Project Period (FY)
1997 – 1999
Completed (Fiscal Year 1999)
|Budget Amount *help
¥5,500,000 (Direct Cost: ¥5,500,000)
Fiscal Year 1999: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1998: ¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1997: ¥2,300,000 (Direct Cost: ¥2,300,000)
|Keywords||Mixed Reality / Fusion of Real and Virtual / Geometric Registration / Binocular Stereo / Motion Stereo / 3D Structure Reconstruction / Immersive Modeler / Video See-through Augmented Reality / ビデオシースルー複合現実|
We have obtained the following research results in this project.
1.Acquiring 3D Information of a Real Scene by Binocular Stereo
One of the most important problems in augmented reality is to resolve occlusions between real and virtual objects. The problem requires depth information of a real world scene. We have studied on improving the efficiency of stereo matching. Our idea for improving the efficiency is to limit stereo matching areas to those on which virtual objects are merged. This made it possible to estimate depth of real world in real time.
2.Acquiring 3D Information of a Real Scene by Motion Stereo
A new factorization method was developed for estimating 3D structure of a real scene from a sequence of images obtained by a moving camera. Another attempt is to predict apparent motion in dynamic images, which improves the efficiency of stereo matching.
3.Generation of Virtual Objects by Immersive Modeler
We have extended the immersive solid modeler VLEGO for generating virtual objects in natural and simple way. Also developed is a technique for imposing geometric constraints on virtual objects. This made it possible to create articulated objects and to generate animations.
4.Merging Virtual Objects into a Real World Scene Image with Correct Occlusion
Geometric registration between real and virtual worlds was achieved by tracking markers in captured images. This may be called a vision-based registration. Integrating this result with those in above items, we have developed an efficient method of stereo image composition.
5.Development of Prototype System for Merging Real and Virtual
We have developed a prototype of stereoscopic video see-through HMD which can merge real and virtual objects with correct occlusion in real time. Experiments have shown the feasibility of the prototype systems. The displayed image of merging real and virtual is updated every 100ms.