Name
Title | ||
|---|---|---|
Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes. |
Abstract | ||
|---|---|---|
This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-20867-7_29 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Sampling density,Signal processing,Data Applied,Pattern recognition,Mathematical morphology,Computer science,Segmentation,Real-time computing,Artificial intelligence,Operator (computer programming),Point cloud | Conference | 11564 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Teo Asplund | 1 | 0 | 0.34 |
| Andrés Serna | 2 | 36 | 4.57 |
| Beatriz Marcotegui | 3 | 212 | 23.17 |
| Robin Strand | 4 | 307 | 28.17 |
| Cris L Luengo Hendriks | 5 | 125 | 13.99 |