Shape-reserved stereo matching with segment-based cost aggregation and dual-path refinement

Chih Shuan Huang, Ya Han Huang, Din Yuen Chan, Jar Ferr Yang

研究成果: Article同行評審

14 引文 斯高帕斯(Scopus)

摘要

Stereo matching is one of the most important topics in computer vision and aims at generating precise depth maps for various applications. The major challenge of stereo matching is to suppress inevitable errors occurring in smooth, occluded, and discontinuous regions. In this paper, the proposed stereo matching system uses segment-based superpixels and matching cost. After determination of edge and smooth regions and selection of matching cost, we suggest the segment-based adaptive support weights in cost aggregation instead of color similarity and spatial proximity only. The proposed dual-path depth refinements use the cross-based support region by referring texture features to correct the inaccurate disparities with iterative procedures to improve the depth maps for shape reserving. Specially for leftmost and rightmost regions, the segment-based refinement can greatly improve the mismatched disparity holes. The experimental results show that the proposed system can achieve higher accurate depth maps than the conventional methods.

原文English
文章編號38
期刊Eurasip Journal on Image and Video Processing
2020
發行號1
DOIs
出版狀態Published - 2020 12月 1

All Science Journal Classification (ASJC) codes

  • 訊號處理
  • 資訊系統
  • 電氣與電子工程

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