ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W4, 47-54, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
11 Mar 2015
A. Hervieu, B. Soheilian, and M. Brédif Université Paris-Est, IGN, SRIG, MATIS, 73 avenue de Paris, 94160 Saint Mandé, France
Keywords: RJ-MCMC, Prior-driven, Data-driven, Road marking, Image Abstract. 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.
Conference paper (PDF, 2582 KB)

Citation: Hervieu, A., Soheilian, B., and Brédif, M.: ROAD MARKING EXTRACTION USING A MODEL&DATA-DRIVEN RJ-MCMC, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W4, 47-54,, 2015.

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