Name
Abstract | ||
|---|---|---|
Reconstructing 3D objects by gathering information from multiple spatial viewpoints is a fundamental problem in a variety of applications ranging from heritage reconstruction to industrial image processing. A central issue is known as the "point set registration or matching" problem. where the two sets being considered are to be rigidly aligned. This is a complex problem with a huge search space that suffers from high computational costs or requires expensive and bulky hardware to be added to the scanning system. To address these issues, a hybrid hardware-software approach was presented in (Pribanic et al., 2016) allowing for fast software registration by using commonly available (smartphone) sensors. In this paper we present hierarchical techniques to improve the performance of this algorithm. Additionally, we compare the performance of our algorithm against other approaches. Experimental results using real data show how the algorithm presented greatly improves the time of the previous algorithm and perform best over all studied algorithms. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.5220/0006112600440051 | PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4 |
Keywords | Field | DocType |
Point Cloud Matching, Algorithms and Data Structures, Regular Grid, Hierarchical Approach | Computer vision,Computer science,Artificial intelligence,Point cloud | Conference |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ferran Roure | 1 | 17 | 2.77 |
| Xavier Llado | 2 | 578 | 40.04 |
| Joaquim Salvi | 3 | 1443 | 93.90 |
| Tomislav Pribanic | 4 | 198 | 16.94 |
| Yago Diez | 5 | 45 | 11.50 |