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Disparity map refinement method based on Markov random field

A Markov random field and disparity map technology, applied in the field of computer vision and pattern recognition, can solve problems such as no very effective solutions, and achieve the effect of improving accuracy

Active Publication Date: 2015-10-07
LANZHOU UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

How can I "remove" these outliers in the disparity map? There is currently no very effective solution

Method used

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  • Disparity map refinement method based on Markov random field
  • Disparity map refinement method based on Markov random field
  • Disparity map refinement method based on Markov random field

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Embodiment 1

[0048] The refinement method of disparity map based on Markov random field of the present invention comprises the following steps:

[0049] (1) Read the initial left disparity map. The initial left disparity map is obtained by a certain stereo matching algorithm. For example, a global stereo matching algorithm such as trust propagation algorithm, graph cut algorithm, etc. can be used;

[0050] (2) Generate the right disparity map, and use the left and right correspondence principle of stereo matching, that is, the corresponding right disparity map can be generated according to the left disparity map;

[0051] (3) Abnormal parallax point detection;

[0052] (4) Parallax point classification;

[0053] (5) Establish a Markov random field model;

[0054] (6) Establish the global energy equation;

[0055] (7) Calculation of data items and smoothing items;

[0056] (8) Use the graph cut algorithm to solve;

[0057] (9) Obtain a high-precision disparity map after refinement.

[0...

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Abstract

A disparity map refinement method based on a Markov random field is provided by the invention and belongs to the technical fields of computer vision and pattern recognition, comprising steps of: inputting an initial left disparity map and obtaining a right disparity map; performing outlier detection by using an extended cross validation method and classifying disparity points; establishing a global energy function; calculating a data item and a smoothing item; solving with a graph cut algorithm; and obtaining a refined disparity map. According to the invention, the disparity map refinement method based on a Markov random field can be used to effectively remove mismatched points in the disparity map generated by a local or global stereo matching algorithm and greatly improve accuracy of the disparity map, so as to finally obtain a refined high accuracy disparity map, which facilitates further treatment of visual depth information.

Description

technical field [0001] The invention relates to the technical field of computer vision and pattern recognition, in particular to a method for refining a disparity map in stereo vision technology. Background technique [0002] The stereo matching problem is a key scientific problem in computer vision, and there is no completely satisfactory solution so far. Many algorithms trade off matching efficiency and accuracy for different applications. Here we only discuss how to further improve the accuracy of stereo matching. [0003] Given two corrected stereo image pairs, when a certain algorithm is used to solve the stereo matching problem, the result of the algorithm is often a left disparity map or two left and right disparity maps. Due to the influence of various complex factors such as occlusion, there are always more or less mismatches in the obtained disparity map. The performance of these mismatches in the disparity map is a lot of outliers, and some outliers are even ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T2207/20228
Inventor 何俊学
Owner LANZHOU UNIVERSITY OF TECHNOLOGY
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