Sampling the disparity space image

Richard Szeliski and Daniel Scharstein

Abstract

A central issue in stereo algorithm design is the choice of matching cost. Many algorithms simply use squared or absolute intensity differences based on integer disparity steps. In this paper, we address potential problems with such approaches. We begin with a careful analysis of the properties of the continuous disparity space image (DSI) and propose several new matching cost variants based on symmetrically matching interpolated image signals. Using stereo images with ground truth, we empirically evaluate the performance of the different cost variants and show that proper sampling can yield improved matching performance.

Details

Publication typeArticle
Published inIEEE Transactions on Pattern Analysis and Machine Intelligence
Pages419-425
Volume26
Number3
PublisherIEEE Computer Society
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