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Stereo matching algorithm for computer vision

A computer vision and stereo matching technology, applied in computing, image data processing, image enhancement and other directions, can solve the problems of low parallax accuracy and large noise interference, achieve low computational complexity, reduce false matching rate, and good effect. Effect

Pending Publication Date: 2018-11-20
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art, provide a computer vision stereo matching algorithm, and solve the problems of low parallax precision and large noise interference in the existing binocular stereo matching method

Method used

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  • Stereo matching algorithm for computer vision
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Embodiment Construction

[0017] The specific implementation of the present invention will be further described in detail below in conjunction with the accompanying drawings of the embodiments, so as to make the technical solution of the present invention easier to understand and grasp, so as to define and support the protection scope of the present invention more clearly.

[0018] Such as figure 1 As shown, the present invention regards the calculation of the matching cost as a supervised learning process, calculates the initial matching cost by training a fully connected neural network model, and uses the WTA strategy to generate the initial disparity map. This method specifically comprises the following steps:

[0019] Construct a training data set: process the stereo image pairs in the training data set to construct training samples. Each training sample includes two parts, namely the left and right image blocks, the left image block is an image block with a size of 11x11 in the left image, and th...

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Abstract

The invention discloses a stereo matching algorithm for computer vision, which is implemented based on a fully connected neural network and Edge-aware Disparity Propagation (EDP). The stereo matchingalgorithm comprises the steps of: firstly, calculating the initial matching cost of an input stereo image pair through a fully connected neural network, and using the WTA algorithm to find a corresponding disparity value, and generating an initial disparity map; performing consistency detection, and using the EDP algorithm and geodetic distance filtering to reconstruct the matching cost of a disparity inconsistent region, obtaining a new disparity value of the inconsistent region, and filling the new disparity value into a hole disparity map to obtain a complete disparity map; and finally, generating a final disparity map through sub-pixel enhancement optimization. Experimental values show that the algorithm can effectively reduce the mismatch rate of stereo matching and improve the accuracy of the disparity map, has lower mismatch rate especially in a non-occlusion region.

Description

technical field [0001] The invention relates to a stereo matching algorithm based on a fully connected neural network and edge-aware parallax propagation, and belongs to the field of binocular stereo vision of computer vision. Background technique [0002] In recent years, stereo vision research, as the most important branch of computer vision, has been applied in many popular research fields, such as robot navigation, automobile automatic driving, medical image diagnosis and assisted surgery, etc. Stereo vision is mainly divided into four steps: image acquisition, stereo correction, stereo matching and 3D reconstruction. [0003] Among them, stereo matching is the most important and also the most difficult link. Traditional stereo matching algorithms generally include the following four steps: constructing matching costs, cost aggregation, disparity value calculation, and disparity map optimization. Stereo matching algorithms are mainly divided into two categories: local ...

Claims

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Application Information

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IPC IPC(8): G06T7/30G06N3/04
CPCG06T7/30G06T2207/20081G06T2207/10012G06N3/045
Inventor 霍智勇严邓涛
Owner NANJING UNIV OF POSTS & TELECOMM
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