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An improved non-local cost aggregation method for stereo matching based on color and boundary cue

Dongming Chen 1 Mohsen Ardabilian 1 Xiaofang Wang 1 Liming Chen 1 
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Recently, a novel Non-Local Cost Aggregation (NLCA) algorithm based on a minimum spanning tree (MST) has been proposed for stereo matching providing extremely low computational complexity and outstanding performance. However, since the MST is constructed only based on color cue, this approach suffers from some improper connections at the boundaries of two objects with similar color distribution. In this paper, we propose a new weight function which includes not only the color cue but also the boundary cue of the reference image. Because the boundary cue is more discriminative than the color cue to distinguish the object from the background with similar color, the previous improper connections can be avoided and a more faithful MST can be constructed. Experimental results performed on Middlebury benchmark demonstrate the effectiveness of the improvements. The improved algorithm achieves rank 18th out of 143 submissions, while the original algorithm ranks 31th.
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Submitted on : Tuesday, June 20, 2017 - 9:03:53 AM
Last modification on : Tuesday, June 1, 2021 - 2:08:09 PM


  • HAL Id : hal-01542693, version 1


Dongming Chen, Mohsen Ardabilian, Xiaofang Wang, Liming Chen. An improved non-local cost aggregation method for stereo matching based on color and boundary cue. IEEE International Conference on Multimedia and Expo (ICME), Jul 2013, San Jose, California, USA, United States. ⟨hal-01542693⟩



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