ROAD MARKING EXTRACTION USING A MODEL&DATA-DRIVEN RJ-MCMC
We propose an integrated bottom-up/top-down approach to road-marking extraction from image space. It is based on energy minimization using marked point processes. A generic road marking object model enable us to define universal energy functions that handle various types of road-marking objects (das...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-03-01
|
| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W4/47/2015/isprsannals-II-3-W4-47-2015.pdf |
| Summary: | We propose an integrated bottom-up/top-down approach to road-marking extraction from image space. It is based on energy minimization
using marked point processes. A generic road marking object model enable us to define universal energy functions that handle
various types of road-marking objects (dashed-lines, arrows, characters, etc.). A RJ-MCMC sampler coupled with a simulated annealing
is applied to find the configuration corresponding to the minimum of the proposed energy. We used input data measurements to
guide the sampler process (data driven RJ-MCMC). The approach is enhanced with a model-driven kernel using preprocessed autocorrelation
and inter-correlation of road-marking templates, in order to resolve type and transformation ambiguities. The method is
generic and can be applied to detect road-markings in any orthogonal view produced from optical sensors or laser scanners from aerial
or terrestrial platforms. We show the results an ortho-image computed from ground-based laser scanning. |
|---|---|
| ISSN: | 2194-9042 2194-9050 |