This paper proposes an effective matching strategy to reconstruct 3-D urban models in densely built-up areas. Proposed scheme includes two main steps: feature-based image matching using building recognition technique and 3-D building reconstruction using the refined Rational Function Coefficients (RFCs). Especially, our approach is focused on improving the matching efficiency in complex urban scenes. For this purpose, we first performed automatic building recognition between stereo images, and then we endowed all points of building edges with identifiers using edge tracing method. Each identifier plays an important role in reducing search space for image matching within points of same building. A standard IKONOS stereo product was used to evaluate the proposed algorithms. It turned out that the proposed method could automatically determine the initial position and could dramatically reduce search space for point matching. Also, it was demonstrated that the updated RFCs could provide high-quality 3-D urban models.