scholarly journals A QUBO Formulation of the Stereo Matching Problem for D-Wave Quantum Annealers

Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 786 ◽  
Author(s):  
William Cruz-Santos ◽  
Salvador Venegas-Andraca ◽  
Marco Lanzagorta
Keyword(s):  
Computer Vision ◽  
Experimental Validation ◽  
Stereo Matching ◽  
Stereo Pair ◽  
Quantum Annealing ◽  
Matching Problem ◽  
Random Dot Stereograms ◽  
Qubo Formulation ◽  
Min Cut ◽  
D Wave

In this paper, we propose a methodology to solve the stereo matching problem through quantum annealing optimization. Our proposal takes advantage of the existing Min-Cut/Max-Flow network formulation of computer vision problems. Based on this network formulation, we construct a quadratic pseudo-Boolean function and then optimize it through the use of the D-Wave quantum annealing technology. Experimental validation using two kinds of stereo pair of images, random dot stereograms and gray-scale, shows that our methodology is effective.

scholarly journals Benchmarking Quantum Annealing Against “Hard” Instances of the Bipartite Matching Problem

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Daniel Vert ◽  
Renaud Sirdey ◽  
Stéphane Louise
Keyword(s):  
Simulated Annealing ◽  
Polynomial Time ◽  
Optimal Solution ◽  
Quantum Computers ◽  
Quantum Annealing ◽  
Maximum Cardinality ◽  
Matching Problem ◽  
Bipartite Matching ◽  
Wave Device ◽  
D Wave

AbstractThis paper experimentally investigates the behavior of analog quantum computers as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem which is specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and hence provides additional evidences suggesting that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality. Additionally, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide evidences that the sparsity of these topologies which, as such, lead to QUBO problems of artificially inflated sizes can partly explain the aforementioned disappointing observations. Therefore, this paper hints that denser interconnection topologies are necessary to unleash the potential of the quantum annealing approach.

scholarly journals A HOLISTIC APPROACH FOR INSPECTION OF CIVIL INFRASTRUCTURES BASED ON COMPUTER VISION TECHNIQUES

2016 ◽  
Vol XLI-B5 ◽  
pp. 131-138 ◽  
Author(s):  
C. Stentoumis ◽  
E. Protopapadakis ◽  
A. Doulamis ◽  
N. Doulamis
Keyword(s):  
Computer Vision ◽  
Stereo Matching ◽  
State Of The Art ◽  
Holistic Approach ◽  
Structural Defects ◽  
Stereo Pair ◽  
Detection Scheme ◽  
Civil Infrastructures ◽  
Continuous State ◽  
Operational Life

In this work, it is examined the 2D recognition and 3D modelling of concrete tunnel cracks, through visual cues. At the time being, the structural integrity inspection of large-scale infrastructures is mainly performed through visual observations by human inspectors, who identify structural defects, rate them and, then, categorize their severity. The described approach targets at minimum human intervention, for autonomous inspection of civil infrastructures. The shortfalls of existing approaches in crack assessment are being addressed by proposing a novel detection scheme. Although efforts have been made in the field, synergies among proposed techniques are still missing. The holistic approach of this paper exploits the state of the art techniques of pattern recognition and stereo-matching, in order to build accurate 3D crack models. The innovation lies in the hybrid approach for the CNN detector initialization, and the use of the modified census transformation for stereo matching along with a binary fusion of two state-of-the-art optimization schemes. The described approach manages to deal with images of harsh radiometry, along with severe radiometric differences in the stereo pair. The effectiveness of this workflow is evaluated on a real dataset gathered in highway and railway tunnels. What is promising is that the computer vision workflow described in this work can be transferred, with adaptations of course, to other infrastructure such as pipelines, bridges and large industrial facilities that are in the need of continuous state assessment during their operational life cycle.

scholarly journals A HOLISTIC APPROACH FOR INSPECTION OF CIVIL INFRASTRUCTURES BASED ON COMPUTER VISION TECHNIQUES

2016 ◽  
Vol XLI-B5 ◽  
pp. 131-138 ◽  
Author(s):  
C. Stentoumis ◽  
E. Protopapadakis ◽  
A. Doulamis ◽  
N. Doulamis
Keyword(s):  
Computer Vision ◽  
Stereo Matching ◽  
State Of The Art ◽  
Holistic Approach ◽  
Structural Defects ◽  
Stereo Pair ◽  
Detection Scheme ◽  
Civil Infrastructures ◽  
Continuous State ◽  
Operational Life

In this work, it is examined the 2D recognition and 3D modelling of concrete tunnel cracks, through visual cues. At the time being, the structural integrity inspection of large-scale infrastructures is mainly performed through visual observations by human inspectors, who identify structural defects, rate them and, then, categorize their severity. The described approach targets at minimum human intervention, for autonomous inspection of civil infrastructures. The shortfalls of existing approaches in crack assessment are being addressed by proposing a novel detection scheme. Although efforts have been made in the field, synergies among proposed techniques are still missing. The holistic approach of this paper exploits the state of the art techniques of pattern recognition and stereo-matching, in order to build accurate 3D crack models. The innovation lies in the hybrid approach for the CNN detector initialization, and the use of the modified census transformation for stereo matching along with a binary fusion of two state-of-the-art optimization schemes. The described approach manages to deal with images of harsh radiometry, along with severe radiometric differences in the stereo pair. The effectiveness of this workflow is evaluated on a real dataset gathered in highway and railway tunnels. What is promising is that the computer vision workflow described in this work can be transferred, with adaptations of course, to other infrastructure such as pipelines, bridges and large industrial facilities that are in the need of continuous state assessment during their operational life cycle.

scholarly journals Disparity Map Generation from Illumination Variant Stereo Images Using Efficient Hierarchical Dynamic Programming

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Viral H. Borisagar ◽  
Mukesh A. Zaveri
Keyword(s):  
Dynamic Programming ◽  
Stereo Matching ◽  
Stereo Image ◽  
Stereo Pair ◽  
Image Pair ◽  
Stereo Images ◽  
Disparity Map ◽  
Illumination Variation ◽  
Matching Problem ◽  
Wide Range

A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.

An Improved Quantum Solution for the Stereo Matching Problem

2021 ◽  
Author(s):  
Shahrokh Heidari ◽  
Mitchell Rogers ◽  
Patrice Delmas
Keyword(s):  
Stereo Matching ◽  
Matching Problem ◽  
Quantum Solution

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

scholarly journals Quantum annealing algorithms for track pattern recognition

2020 ◽  
Vol 245 ◽  
pp. 10006
Author(s):  
Masahiko Saito ◽  
Paolo Calafiura ◽  
Heather Gray ◽  
Wim Lavrijsen ◽  
Lucy Linder ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Simulated Annealing ◽  
Hadron Collider ◽  
Recognition Algorithm ◽  
Quantum Annealing ◽  
Discovery Potential ◽  
Energy Frontier ◽  
Track Pattern ◽  
Annealing Algorithms ◽  
D Wave

The High-Luminosity Large Hadron Collider (HL-LHC) starts from 2027 to extend the physics discovery potential at the energy frontier. The HL-LHC produces experimental data with a much higher luminosity, requiring a large amount of computing resources mainly due to the complexity of a track pattern recognition algorithm. Quantum annealing might be a solution for an efficient track pattern recognition in the HL-LHC environment. We demonstrated to perform the track pattern recognition by using the D-Wave annealing machine and the Fujitsu Digital Annealer. The tracking efficiency and purity for the D-Wave quantum annealer are comparable with those for a classical simulated annealing at a low pileup condition, while a drop in performance is found at a high pileup condition, corresponding to the HL-LHC pileup environment. The tracking efficiency and purity for the Fujitsu Digital Annealer are nearly the same as the classical simulated annealing.

scholarly journals A comparison of semiglobal and local dense matching algorithms for surface reconstruction

2014 ◽  
Vol XL-5 ◽  
pp. 187-194 ◽  
Author(s):  
E. Dall'Asta ◽  
R. Roncella
Keyword(s):  
Computer Vision ◽  
Stereo Matching ◽  
Least Square ◽  
Stereo Image ◽  
Dense Matching ◽  
Consistency Constraints ◽  
Global Matching ◽  
Matching Cost ◽  
Software Codes ◽  
Matching Techniques

Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision.<br><br> The paper is focused on the comparison of some stereo matching algorithms (local and global) which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM), which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed.<br><br> The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan) and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

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