Cost aggregation with anisotropic diffusion in feature space for hybrid stereo matching

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a cost aggregation using anisotropic diffusion on a feature space for hybrid stereo matching. Stereo matching can be classified into two categories: feature-based and area-based approaches. Feature-based approaches generate accurate but sparse disparity maps. On the other hand, area-based approaches generate dense but unreliable disparity maps, especially at depth discontinuities and homogeneous regions. We hence propose a stereo matching algorithm having advantages of both approaches. We study how to design a correspondence algorithm without modeling any depth cues except disparity. A procedure of depth perception is modeled via anisotropic diffusion on the feature space in terms of coherence. Based on the assumption that similar local feature space has similar disparity, we define the feature space and its similarity and then introduce feature confidences into the proposed model. Experimental results show that the performance of the proposed method is comparable to that of the state-of-the-art methods.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages3365-3368
Number of pages4
DOIs
Publication statusPublished - 2011 Dec 1
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 2011 Sep 112011 Sep 14

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period11/9/1111/9/14

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All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Ham, B., Min, D., & Sohn, K. (2011). Cost aggregation with anisotropic diffusion in feature space for hybrid stereo matching. In ICIP 2011: 2011 18th IEEE International Conference on Image Processing (pp. 3365-3368). [6116393] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2011.6116393