TY - JOUR
T1 - Accurate stereo matching by two-step energy minimization
AU - Mozerov, Mikhail G.
AU - Van De Weijer, Joost
PY - 2015/3/1
Y1 - 2015/3/1
N2 - © 2014 IEEE. In stereo matching, cost-filtering methods and energy-minimization algorithms are considered as two different techniques. Due to their global extent, energy-minimization methods obtain good stereo matching results. However, they tend to fail in occluded regions, in which cost-filtering approaches obtain better results. In this paper, we intend to combine both the approaches with the aim to improve overall stereo matching results. We show that a global optimization with a fully connected model can be solved by cost-filtering methods. Based on this observation, we propose to perform stereo matching as a two-step energy-minimization algorithm. We consider two Markov random field (MRF) models: 1) a fully connected model defined on the complete set of pixels in an image and 2) a conventional locally connected model. We solve the energy-minimization problem for the fully connected model, after which the marginal function of the solution is used as the unary potential in the locally connected MRF model. Experiments on the Middlebury stereo data sets show that the proposed method achieves the state-of-the-arts results.
AB - © 2014 IEEE. In stereo matching, cost-filtering methods and energy-minimization algorithms are considered as two different techniques. Due to their global extent, energy-minimization methods obtain good stereo matching results. However, they tend to fail in occluded regions, in which cost-filtering approaches obtain better results. In this paper, we intend to combine both the approaches with the aim to improve overall stereo matching results. We show that a global optimization with a fully connected model can be solved by cost-filtering methods. Based on this observation, we propose to perform stereo matching as a two-step energy-minimization algorithm. We consider two Markov random field (MRF) models: 1) a fully connected model defined on the complete set of pixels in an image and 2) a conventional locally connected model. We solve the energy-minimization problem for the fully connected model, after which the marginal function of the solution is used as the unary potential in the locally connected MRF model. Experiments on the Middlebury stereo data sets show that the proposed method achieves the state-of-the-arts results.
KW - bilateral filter
KW - energy minimization
KW - fully connected MRF model
KW - Stereo matching
U2 - 10.1109/TIP.2015.2395820
DO - 10.1109/TIP.2015.2395820
M3 - Article
SN - 1057-7149
VL - 24
SP - 1153
EP - 1163
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
IS - 3
M1 - 7018068
ER -