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This work presents two techniques for computing dense disparity maps from two or more images. These methods are exploited in an application of augmented reality in order to add a virtual object with proper occlusions in the real scene. The proposed stereo matching techniques are based on area matching. We first present an implementation of the dynamic programming which produces a high quality of dense disparity map. Furthermore, in order to improve both the time computing and the map quality, we propose a hierarchical approach which combines the multi-resolution and the dynamic programming. The disparity maps thus obtained are applied in augmented reality in order to integrate in a realistic way the virtual objects. The applicability of the method is shown on many sequences of images.