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| Content Provider | ACM Digital Library |
|---|---|
| Author | Kuijper, Arjan Yoon, Sang Min Bustos, Benjamin Schreck, Tobias Scherer, Maximilian Walter, Michael |
| Abstract | 3D Object Retrieval is an important field of research with many application possibilities. One of the main goals in this research is the development of discriminative methods for similarity search. The descriptor-based approach to date has seen a lot of research attention, with many different extraction algorithms proposed. In previous work, we have introduced a simple but effective scheme for 3D model retrieval based on a spatially fixed combination of 3D object fragment descriptors. In this work, we propose a novel flexible combination scheme based on finding the best matching fragment descriptors to use in the combination. By an exhaustive experimental evaluation on established benchmark data we show the capability of the new combination scheme to provide improved retrieval effectiveness. The method is proposed as a versatile and inexpensive method to enhance the effectiveness of a given global 3D descriptor approach. |
| Starting Page | 23 |
| Ending Page | 28 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450311311 |
| DOI | 10.1145/2155555.2155559 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-02-22 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | 3d object retrieval Effectiveness Descriptor combinations |
| Content Type | Text |
| Resource Type | Article |
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