A Combined Approach for Stereoscopic 3D Reconstruction Model based on Improved Semi Global Matching

The effective recovery of the 3D structure of a scene using two or more 2D images of the scene, each acquired from a different viewpoint is a challenging task of stereovision. Defining pixel correspondence in stereo pairs is a fundamental process for automated image based effective 3D reconstruction. This paper presents modified Census based approach for local cost optimization where local matching cost is combined with Sum of Squared Absolute Differences (SSAD) of the image color values and then aggregated. From the aggregated cost, effective disparity map is obtained using Semi Global Matching (SGM) which improves the quality of the matches. This proposed approach represents a fusion of state of the art algorithms to improve the matching quality with reduced number of bad pixels. Finally, a stereoscopic 3D view will be obtained by merging triangulation algorithm in the realistic manner. Because of more realistic depth perception, our proposed three dimensional stereo models finds application in medical field where it improves surgical success with shorter operation time and research in space where effective analysis can be made by using calibrated photo realistic 3D model of the space structure.