2001 Fiscal Year Final Research Report Summary
Research on 3D Moving Object Databases
| Project/Area Number |
11480085
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
情報システム学(含情報図書館学)
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| Research Institution | Ochanomizu University |
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Principal Investigator |
MASUNAGA Yoshifumi Ochanomizu University, Department of Information Science, Professor, 理学部, 教授 (70006261)
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| Project Period (FY) |
1999 – 2001
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| Keywords | database / moving object / three dimensional space / data model / MOQL / similarity search |
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| Research Abstract |
This research investigated a theory and practice of a moving object database system that is rile to answer to a variety of queries on moves of moving objects such as human and automobiles. First we proposed a moving object data model that can describe the spatio-temporal characteristics of moving objects. It describes not only the centroid position of a moving object but also its direction and orientation as the data of move, it also describes the orbit of a moving object as well as the spatial relationships between two moving objects such as the distance, the mutual direction and the topological relationship. We proposed a moving object query language named MOQL by which we can specify a variety of object moves. However, we found that there was a difficulty when we use WOOL to specify a dynamic move such as an object move moving like this. In order to resolve this problem, we introduce a motion capturing system to capture an object move as a sample move by which the system can retrieve a set of objects whose move are similar to this sample. We have introduced the identity, the basic similarity, the partial similarity, the similarity under time warping, and the spatio-temporal similarity of two moving objects. As a result it is shown that our basic similarity definition can distinguish two object move shaving different moving speed patterns but have the same orbit. However, it is also revealed that we must introduce a new type of a similarity definition that can distinguish the speed patterns of moving objects. It is shown that the definition of the similarity based on time warping works better when an object move is divided into a set of component objects.
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