Stereo Matching Algorithm Based on Detecting Feature Points

2012 ◽  
Vol 433-440 ◽  
pp. 6190-6194
Author(s):  
Shuo Bo Xu ◽  
Di Shi Xu ◽  
Hua Fang
Keyword(s):  
Stereo Matching ◽  
Characteristic Point ◽  
Feature Points ◽  
Epipolar Line ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Characteristic Points ◽  
Left And Right ◽  
Straight Lines ◽  
Verification Strategy

A new method for solving the stereo matching problem in the presence of large occlusion is presented. This method for stereo matching and occlusion detection is based on searching disparity point. In this paper, we suppose that a pair of epipolar-line images is a projection of a group of piece-wise straight lines on the left and right images respective. Therefore the disparity curve corresponding to a pair of epipolar-line images may be approximated by a group of piece-wise straight lines. Then the key of solving disparity curve is how to get the “characteristic points” on the group of piece-wise straight lines. Based on this view, we fetched out the conception “disparity point”, and three kinds of special disparity points are correctly corresponding to the “characteristic point”. By analyzing intensity property of a disparity point and its neighbor points, an approach which combines stepwise hypothesis-verification strategy with three constraint conditions is devised to extract the candidate disparity points from the epipolar images.

Matching Algorithm of Binocular Dynamic Vision Measurement

2013 ◽  
Vol 278-280 ◽  
pp. 764-770
Author(s):  
Xue Qi Sun ◽  
Ming Li Dong ◽  
Jun Wang
Keyword(s):  
Measurement System ◽  
Feature Points ◽  
Epipolar Line ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Vision Measurement ◽  
Dynamic Vision ◽  
Disparity Gradient ◽  
Relationship Of ◽  
Double Constraint

In order to realize the correspondence of feature points in the binocular dynamic vision measurement system, the two homologous images matching problem in the paper is studied. First of all, a method of strong space resection. The strong space resection optimizes the elements of exterior orientation, improves the precision, so as to improve the calculating precision of epipolar line. Secondly, an algorithm of multiple restriction matching which is for two homologous images matching of feature points has been introduced. This algorithm based on epipolar line constrain, increases the uniqueness constraint and double constraint, combined with the second match with disparity gradient constrain, finally get the correct matching relationship of feature points in two homologous images. The experimental results show that: this method for matching of binocular dynamic vision measurement system, can get 100% of the matching accuracy rate. And it would satisfy the need of binocular dynamic vision measurement system.

A New Matching Algorithm Based on Characteristic Points of Epipolar Line

2014 ◽  
Vol 522-524 ◽  
pp. 1166-1170
Author(s):  
Ai Hua Xu ◽  
An Tao ◽  
Jia Jing Zhuo ◽  
Lan Qiong Sun
Keyword(s):  
Aerial Images ◽  
Epipolar Line ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Calculation Time ◽  
Image Sampling ◽  
Characteristic Points ◽  
Images Processing

The characteristic points matching is the hot point in the aerial images processing. The matching algorithm of characteristic points based on epipolar line was put forward according to the characteristics of aerial images. This algorithm overcomes some problems in the process of image sampling, solves the matching problem of untextured regions better, and deletes the dissimilarity points, shortens the calculation time greatly as well.

A New Binocular Vision Stereo Matching Algorithm

2013 ◽  
Vol 389 ◽  
pp. 721-725 ◽  
Author(s):  
Hui Zhang ◽  
Ling Tao Zhang ◽  
Li Wang
Keyword(s):  
Binocular Vision ◽  
Stereo Matching ◽  
Computational Cost ◽  
Large Data ◽  
Feature Points ◽  
Canny Operator ◽  
Matching Algorithm ◽  
Long Time ◽  
Image Edge ◽  
Left And Right

With the shortcomings of the large data amount and long time consuming in the conventional binocular vision stereo matching algorithm, a new fast stereo matching algorithm is presented in this paper. It is fast computed based on the line moments and angle vector .Firstly, the method detects image edge using canny operator, and finds the target objects according line moments, then the object contours feature points are extracted. Finally, using angle vector to realize the corresponding pixel matching in the left and right image .The algorithm effectively reduces the computational complexity, computational cost is decreased greatly. The experimental results show that the algorithm is possible and valid.

scholarly journals Stereo Matching Based on Immune Neural Network in Abdomen Reconstruction

2015 ◽  
Vol 2015 ◽  
pp. 1-15
Author(s):  
Huan Liu ◽  
Kuangrong Hao ◽  
Yongsheng Ding ◽  
Chunjuan Ouyang
Keyword(s):  
Neural Network ◽  
Stereo Matching ◽  
Feature Matching ◽  
Three Dimensional ◽  
Target Point ◽  
Feature Points ◽  
Matching Algorithm ◽  
Optimization Task ◽  
Feasible Alternative ◽  
Single Neural Network

Stereo feature matching is a technique that finds an optimal match in two images from the same entity in the three-dimensional world. The stereo correspondence problem is formulated as an optimization task where an energy function, which represents the constraints on the solution, is to be minimized. A novel intelligent biological network (Bio-Net), which involves the human B-T cells immune system into neural network, is proposed in this study in order to learn the robust relationship between the input feature points and the output matched points. A model from input-output data (left reference point-right target point) is established. In the experiments, the abdomen reconstructions for different-shape mannequins are then performed by means of the proposed method. The final results are compared and analyzed, which demonstrate that the proposed approach greatly outperforms the single neural network and the conventional matching algorithm in precise. Particularly, as far as time cost and efficiency, the proposed method exhibits its significant promising and potential for improvement. Hence, it is entirely considered as an effective and feasible alternative option for stereo matching.

Synergetic Stereo Matching Algorithm for Occlusion and Reversal Position

2003 ◽  
Vol 7 (2) ◽  
pp. 178-188 ◽  
Author(s):  
Tohru Irie ◽  
◽  
Hiroshi Maeda ◽  
Norikazu Ikoma
Keyword(s):  
Template Matching ◽  
Order Parameter ◽  
Stereo Matching ◽  
Recognition Algorithm ◽  
Parameter Design ◽  
Pattern Recognition Algorithm ◽  
Matching Algorithm ◽  
Left And Right ◽  
Attention Parameter ◽  
Two Parameters

We propose a stereo matching algorithm based on a pattern recognition algorithm using synergetics. Matching between left and right images is represented by the differential equations with order parameter and attention parameter. This algorithm gives us a free hand designing the two parameters. This paper presents parameter design and experiment results confirming that the proposed algorithm has high matching precision compared to the conventional template matching and DP matching.

A Multi-Gradation Stereo Matching Method Based on Edge Feature Points

2013 ◽  
Vol 748 ◽  
pp. 624-628
Author(s):  
Zhu Lin Li
Keyword(s):  
Object Recognition ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Feature Points ◽  
Image Pair ◽  
Three Dimensional Reconstruction ◽  
Matching Method ◽  
Matching Algorithm ◽  
Dimensional Reconstruction ◽  
Edge Feature

A gradation stereo matching algorithm based on edge feature points was proposed. Its basic idea is: firstly edge feature points of image pair were extracted; then, gradient invariability and singular eigenvalue invariability were analyzed, two-grade stereo matching method was build, foundation matrix was solved further, and three-grade stereo matching algorithm was finished by foundation matrix guidance. The result indicates that the algorithm can improve matching precision, from 58.3% to 73.2%, it is simple and utility, and it is important for object recognition, tracking, and three-dimensional reconstruction.

A Fast Binocular Vision Stereo Matching Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 3735-3738
Author(s):  
Hui Zhang ◽  
Ling Tao Zhang ◽  
Yi Ren
Keyword(s):  
Stereo Matching ◽  
Computational Cost ◽  
Stereo Image ◽  
Feature Points ◽  
Image Pair ◽  
Canny Operator ◽  
Canny Edge Detection ◽  
Matching Algorithm ◽  
Canny Edge ◽  
Image Edge

In this paper we present a fast indoor stereo matching algorithm based on canny edge detection and line moments. We first detect image edge by using Canny operator, then find the target objects according line moments, the feature points of the objects’ contours are extracted. Finally, matching the pixel in stereo image pair according the angle vector. The algorithm effectively reduces the computational complexity, computational cost is decreased greatly. The experimental results show that the algorithm is possible and valid.

Vision-Based Aerial Refueling Docking Based on SURF Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 3102-3106
Author(s):  
Si Yuan Qin ◽  
Jian Guo Yan
Keyword(s):  
Vision System ◽  
Three Dimensional ◽  
Spatial Position ◽  
Target Point ◽  
Feature Points ◽  
Aerial Refueling ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Left And Right

For the Boom and Receptacle Air Refueling, in order to locate the spatial position of the refueling receptacle, an object locating method is developed based on Speeded-up Robust Feature (SURF) algorithm. Firstly, SURF feature vector matching algorithm is used to detect and collect suitable SURF feature points in left and right images produced by binocular stereo vision system separately. Then the point that shows the same spatial position in both left and right images can be located through process such as deleting wrong matching points and calculating the image coordinate of the target point. Finally, the three-dimensional coordinates of the target points could be rebuilt in the camera’s coordinate system. According to the results of experiments, this method has good robustness and practicability.

A Global Stereo Matching Algorithm Based on Adaptive Support-Weight and Graph Cut

2012 ◽  
Vol 151 ◽  
pp. 612-616 ◽  
Author(s):  
Guo He Yu ◽  
Jian Ming Liu ◽  
Xu Sheng Xie ◽  
Ji Guo Zeng
Keyword(s):  
Energy Function ◽  
Stereo Matching ◽  
Graph Cut ◽  
Experimental Results ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Support Weight ◽  
Depth Discontinuity ◽  
Matching Error ◽  
Adaptive Support

For the stereo matching problem in the non-texture, occluded and depth discontinuity regions, a new stereo matching algorithm that based on the adaptive support-weight of Graph Cuts is proposed. It can reduce the matching error in the depth discontinuity and non-texture regions by the single adaptive support-weight matching methods. The occlusion and smoothness penalty is considered by building the energy function. The experimental results show that the proposed algorithm can achieve more precise and reliability matching.

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