Name
Abstract | ||
|---|---|---|
This paper presents an images based 3D model retrieval method in which each model is described by six 2D images. The images are generated by three steps: 1) the model is normalized based on the distribution of the surface normal directions; 2) then, the normalized model is uniformly sampled to generate a number of random points; 3) finally, the random points are projected along six directions to create six images, each of which is described by Zernike moment feature. In the comparison of two models, six images of each model are naturally divided into three pairs, and the similarity between two models is calculated by summing up the distances of all corresponding pairs. The effectiveness of our method is verified by comparative experiments. Meanwhile, high matching speed is achieved, e.g., it takes about 3e-5 seconds to compare two models using a computer with Pentium IV 3.00GHz CPU. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-77409-9_9 | MMM |
Keywords | Field | DocType |
surface normal direction,high matching speed,comparative experiment,pentium iv,corresponding pair,normalized model,model retrieval method,model retrieval approach,zernike moment feature,random point,sampling,projection | Computer vision,Normalization (statistics),Pattern recognition,Computer science,Zernike polynomials,Artificial intelligence,Pentium,Sampling (statistics),Normal | Conference |
Volume | ISSN | ISBN |
4903 | 0302-9743 | 3-540-77407-6 |
Citations | PageRank | References |
3 | 0.40 | 9 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuehong Wang | 1 | 72 | 4.66 |
| Rujie Liu | 2 | 147 | 15.49 |
| Takayuki Baba | 3 | 77 | 8.19 |
| Yusuke Uehara | 4 | 62 | 8.15 |
| Daiki Masumoto | 5 | 76 | 6.33 |
| Shigemi Nagata | 6 | 74 | 7.16 |