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A new 3D reconstruction method based on image dense stereo matching is proposed in this paper. Firstly, the feature-points of stereo images must be extracted by SIFT algorithm and they are matched through similarity constraints. The second step is to select seed points which determine the performance of the algorithm and then we can do dense matching with these seed points. Afterward, the false matches can be eliminated by Symmetrical epipolar distance algorithm and the 3D points coordinates can be calculated in virtue of camera matrix. Finally, the 3D model can be established by Delauny triangulation and texture mapping. Experimental results show that the new method based on dense stereo matching can optimize existing 3D reconstruction method. Moreover, the efficiency and accuracy of the method are both better than those traditional methods based on dense matching.