Stereo Matching via Dual Fusion

Publication Type:
Journal Article
IEEE Signal Processing Letters, 2018, 25 (5), pp. 615 - 619
Issue Date:
Filename Description Size
08318660.pdfPublished Version559.7 kB
Adobe PDF
Full metadata record
© 1994-2012 IEEE. We present a two-fold fusion framework that constructs comprehensive cost volumes for stereo matching. To this end, we develop fusion schemes at two key steps, i.e., a) the raw cost computation and b) the cost aggregation. Specifically, we commence by fusing both structure- and data-oriented features as raw costs. We then incorporate the guided filtered costs into the cross-based cost aggregation and obtain the fused aggregated costs. The fusion schemes at the two steps effectively complement each other and result in an accurate disparity map. Experiments on the Middlebury benchmark v3 demonstrate the state-of-the-art performance of our framework in terms of various metrics.
Please use this identifier to cite or link to this item: