Limiting the Search Range of Correlation Stereo Using Silhouettes

We present a new approach to combine two approaches to three-dimensional reconstruction: silhouette-based and correspondence-based approaches. The two approaches have complementary costs and benefits. Silhouette-based approaches deliver volumetric descriptions which often have very few outliers, but they cannot reconstruct concave surfaces. Correspondence-based approaches give surface descriptions with sub-pixel accuracy, but their search range either allows outliers or falls short of the correct match. We show that a combination of the two can deliver fine-grained accuracy with few outliers. Our specific implementation uses the silhouette reconstruction as prior data to center and bound a stereo search process. We explore the different performance characteristics of the combination and its two component methods qualitatively and quantitatively using