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Sequential Correspondence of Multiple Visual Cues for 3-D Building Reconstruction

Traditional building height estimation from a stereo pair of satellite images relies heavily on the selection of building primitives by the human operator. It is labor-intensive and highly inefficient. In this work, we propose a system to automate the estimation of 3-D building height from an IKONOS stereo pair. Minimum user intervention is required to outline the building top in the left image. Stereo correspondence is automatically established through a multi-scale feature (coarse-to-fine) matching, which is capable of achieving sub-pixel accuracy. The height of the building top is computed using the Rational Polynomial Coefficient (RPC) model. Experimental results show that the proposed method is efficient, robust and it produces accurate building height estimation.