ROAD MARKING EXTRACTION USING A MODEL&DATA-DRIVEN RJ-MCMC
| Autor: | Alexandre Hervieu, Bahman Soheilian, Mathieu Brédif |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
lcsh:Applied optics. Photonics
Laser scanning Computer science business.industry lcsh:T Autocorrelation lcsh:TA1501-1820 Energy minimization lcsh:Technology Transformation (function) Kernel (image processing) lcsh:TA1-2040 Simulated annealing Object model Computer vision Artificial intelligence business lcsh:Engineering (General). Civil engineering (General) Energy (signal processing) |
| Zdroj: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol II-3/W4, Pp 47-54 (2015) |
| ISSN: | 2194-9050 2194-9042 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|