A taxonomy and evaluation of dense two-frame stereo correspondence algorithms-英文文献.pdf

International Journal of Computer Vision 47(1/2/3), 7–42, 2002 c 2002 Kluwer Academic Publishers. Manufactured in The Netherlands. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms DANIEL SCHARSTEIN Department of Mathematics and Computer Science, Middlebury College, Middlebury, VT 05753, USA schar@ RICHARD SZELISKI Microsoft Research, Microsoft Corporation, Redmond, WA 98052, USA szeliski@ Abstract. Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods. Our taxonomy is designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms. We have also produced several new multi-frame stereo data sets with ground truth and are making both the code and data sets available on the Web. Finally, we include a comparative evaluation o