Hybrid approach for accurate depth acquisition with structured light and stereo camera

In this paper, we propose a hybrid approach for accurate depth acquisition by using a structured light-based method with a stereo matching. By projecting additional light patterns onto a scene, a structured light-based method works well on a textureless region where a stereo matching shows poor performance. In contrast, the patterns projected onto a rich textured region obstruct in estimating reliable depth information in the structured light-based method, while a stereo matching excels. We exploit these complementary characteristics by combining the results from both methods that outperform the one from either alone. In our fusion framework, a hybrid stereo matching is introduced, in which the disparity search range for each pixel is limited based on the initial depth map obtained by the structured light-based method. In addition, we introduce a confidence-based fusion method which combines the depth maps, while incorporating the advantages of each method. The experimental results show that the proposed method achieves to estimate accurate depth information, while other methods fail.