Name
Abstract | ||
|---|---|---|
Coarse Matching of point clouds is a fundamental problem in a variety of computer vision applications. While many algorithms have been developed in recent years to address its different aspects, the lack of unified measures and commonly agreed upon data hampers algorithm performances comparison. Additionally, a large number of contributions are tested only with synthetic or processed data. This is a problem as the resulting scenario is somewhat less challenging and does not always conform to practical application conditions. In this paper, we present a new, publicly available database that aims at overcoming the existing problems, provide researchers with a useful tool to compare new contributions to existing ones and represent a step towards standardization. The database contains both processed and unprocessed data with attention to specially challenging datasets. It also includes information on correct solution, presence of noise, overlap percentages and additional information that will allow researchers to focus only on specific parts of the matching pipeline. |
Year | Venue | Field |
|---|---|---|
2015 | VISAPP | Data mining,Pattern recognition,Computer science,Artificial intelligence,Point set,Point cloud,Standardization |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
17 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ferran Roure | 1 | 17 | 2.77 |
| Yago Diez | 2 | 45 | 11.50 |
| Xavier Llado | 3 | 578 | 40.04 |
| Josep Forest | 4 | 326 | 18.23 |
| Tomislav Pribanic | 5 | 198 | 16.94 |
| Joaquim Salvi | 6 | 1443 | 93.90 |