Abstract
The demand for 3D maps of cities and road networks is steadily increasing
and mobile mapping systems are often the preferred acquisition method
for capturing such scenes. Manual processing of point clouds is labour
intensive and thus time consuming and expensive. This article focuses
on the state of the art of automatic classification and 3D mapping of
road objects from point clouds acquired by mobile mapping systems and
considers the feasibility of exploiting scene knowledge to increase the
robustness of classification.
and mobile mapping systems are often the preferred acquisition method
for capturing such scenes. Manual processing of point clouds is labour
intensive and thus time consuming and expensive. This article focuses
on the state of the art of automatic classification and 3D mapping of
road objects from point clouds acquired by mobile mapping systems and
considers the feasibility of exploiting scene knowledge to increase the
robustness of classification.
| Original language | English |
|---|---|
| Pages (from-to) | 16-19 |
| Number of pages | 4 |
| Journal | Geomatics World: the geomatics journal for land, engineering and hydrographic survey |
| Volume | 26 |
| Issue number | 2 |
| Publication status | Published - 2018 |