Name
Abstract | ||
|---|---|---|
Recently, there has been increasing interest in the processing of dynamic scenes as captured by 3D scanners, ideally suited for challenging applications such as immersive tele-presence systems and gaming. Despite the fact that the resolution and accuracy of the modern 3D scanners are constantly improving, the captured 3D point clouds are usually noisy with a perceptive percentage of outliers, stressing the need of an approach with low computational requirements which will be able to automatically remove the outliers and create a consolidated point cloud.In this paper, we introduce a novel method which first recognizes and removes outliers from a dynamic point cloud sequence (DPCS) using a very fast Robust PCA (RPCA) approach and then we use a novel weighted Laplacian interpolation approach to achieve a fast and effective consolidation of a DPCS. Extensive evaluation studies, carried out using a collection of different DPCS, verify that the proposed technique achieves plausible reconstruction output despite the constraints posed by arbitrarily complex motion scenarios. |
Year | Venue | Keywords |
|---|---|---|
2018 | 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 3D point clouds sequence, 3D point cloud outliers, RPCA outliers removal, weighted Laplacian interpolation |
Field | DocType | ISSN |
Computer vision,Pattern recognition,Computer science,Interpolation,Outlier,Coherence (physics),Artificial intelligence,Point cloud,Consolidation (soil),Sparse matrix,Laplace operator | Conference | 1522-4880 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gerasimos Arvanitis | 1 | 9 | 6.21 |
| Aristotelis Spathis-Papadiotis | 2 | 1 | 1.36 |
| Aris S. Lalos | 3 | 192 | 32.84 |
| K. Moustakas | 4 | 285 | 58.02 |
| Nikos Fakotakis | 5 | 31 | 2.74 |