ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W3, 43-48, 2013
https://doi.org/10.5194/isprsannals-II-3-W3-43-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
08 Oct 2013
The Application of a Car Confidence Feature for the Classification of Cross-Roads Using Conditional Random Fields
S. Kosov1, F. Rottensteiner1, C. Heipke1, J. Leitloff2, and S. Hinz2 1Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
2Institute of Photogrammetry and Remote Sensing, Karlsruhe University of Technology, Germany
Keywords: Conditional Random Fields, Contextual, Classification, Crossroads Abstract. The precise classification and reconstruction of crossroads from multiple aerial images is a challenging problem in remote sensing. We apply the Conditional Random Fields (CRF) approach to this problem, a probabilistic model that can be used to consider context in classification. A simple appearance-based model is combined with a probabilistic model of the co-occurrence of class label at neighbouring image sites to distinguish classes that are relevant for scenes containing crossroads. The parameters of these models are learnt from training data. We use multiple overlap aerial images to derive a digital surface model (DSM) and a true orthophoto without moving cars. From the DSM and the orthophoto we derive feature vectors that are used in the classification. Within our framework we make use of a car detector based on support vector machines (SVM), which delivers car probability values. These values are used as additional feature to support the classification when the road surface is occluded by static cars. Our approach is evaluated on a dataset of airborne photos of an urban area by a comparison of the results to reference data. The evaluation is performed for images of different resolution. The method is shown to produce promising results when using the car probability values and higher image resolution.
Conference paper (PDF, 3276 KB)


Citation: Kosov, S., Rottensteiner, F., Heipke, C., Leitloff, J., and Hinz, S.: The Application of a Car Confidence Feature for the Classification of Cross-Roads Using Conditional Random Fields, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W3, 43-48, https://doi.org/10.5194/isprsannals-II-3-W3-43-2013, 2013.

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