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Готові списки джерел за темами / Non-local matching

Добірка наукової літератури з теми "Non-local matching"

Автор: Grafiati

Опубліковано: 7 липня 2024

Оновлено: 7 липня 2024

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Статті в журналах з теми "Non-local matching":

1

Huang, Xu, Yongjun Zhang, and Zhaoxi Yue. "IMAGE-GUIDED NON-LOCAL DENSE MATCHING WITH THREE-STEPS OPTIMIZATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-3 (June 3, 2016): 67–74. http://dx.doi.org/10.5194/isprsannals-iii-3-67-2016.

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This paper introduces a new image-guided non-local dense matching algorithm that focuses on how to solve the following problems: 1) mitigating the influence of vertical parallax to the cost computation in stereo pairs; 2) guaranteeing the performance of dense matching in homogeneous intensity regions with significant disparity changes; 3) limiting the inaccurate cost propagated from depth discontinuity regions; 4) guaranteeing that the path between two pixels in the same region is connected; and 5) defining the cost propagation function between the reliable pixel and the unreliable pixel during disparity interpolation. This paper combines the Census histogram and an improved histogram of oriented gradient (HOG) feature together as the cost metrics, which are then aggregated based on a new iterative non-local matching method and the semi-global matching method. Finally, new rules of cost propagation between the valid pixels and the invalid pixels are defined to improve the disparity interpolation results. The results of our experiments using the benchmarks and the Toronto aerial images from the International Society for Photogrammetry and Remote Sensing (ISPRS) show that the proposed new method can outperform most of the current state-of-the-art stereo dense matching methods.

2

Huang, Xu, Yongjun Zhang, and Zhaoxi Yue. "IMAGE-GUIDED NON-LOCAL DENSE MATCHING WITH THREE-STEPS OPTIMIZATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-3 (June 3, 2016): 67–74. http://dx.doi.org/10.5194/isprs-annals-iii-3-67-2016.

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This paper introduces a new image-guided non-local dense matching algorithm that focuses on how to solve the following problems: 1) mitigating the influence of vertical parallax to the cost computation in stereo pairs; 2) guaranteeing the performance of dense matching in homogeneous intensity regions with significant disparity changes; 3) limiting the inaccurate cost propagated from depth discontinuity regions; 4) guaranteeing that the path between two pixels in the same region is connected; and 5) defining the cost propagation function between the reliable pixel and the unreliable pixel during disparity interpolation. This paper combines the Census histogram and an improved histogram of oriented gradient (HOG) feature together as the cost metrics, which are then aggregated based on a new iterative non-local matching method and the semi-global matching method. Finally, new rules of cost propagation between the valid pixels and the invalid pixels are defined to improve the disparity interpolation results. The results of our experiments using the benchmarks and the Toronto aerial images from the International Society for Photogrammetry and Remote Sensing (ISPRS) show that the proposed new method can outperform most of the current state-of-the-art stereo dense matching methods.

3

Cai, Weibo, Jintao Cheng, Juncan Deng, Yubin Zhou, Hua Xiao, Jian Zhang, and Kaiqing Luo. "Line Segment Matching Fusing Local Gradient Order and Non-Local Structure Information." Applied Sciences 12, no. 1 (December 23, 2021): 127. http://dx.doi.org/10.3390/app12010127.

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Line segment matching is essential for industrial applications such as scene reconstruction, pattern recognition, and VSLAM. To achieve good performance under the scene with illumination changes, we propose a line segment matching method fusing local gradient order and non-local structure information. This method begins with intensity histogram multiple averaging being utilized for adaptive partitioning. After that, the line support region is divided into several sub-regions, and the whole image is divided into a few intervals. Then the sub-regions are encoded by local gradient order, and the intervals are encoded by non-local structure information of the relationship between the sampled points and the anchor points. Finally, two histograms of the encoded vectors are, respectively, normalized and cascaded. The proposed method was tested on the public datasets and compared with previous methods, which are the line-junction-line (LJL), the mean-standard deviation line descriptor (MSLD) and the line-point invariant (LPI). Experiments show that our approach has better performance than the representative methods in various scenes. Therefore, a tentative conclusion can be drawn that this method is robust and suitable for various illumination changes scenes.

4

ZHANG, Chao, Haitian SUN, and Takuya AKASHI. "Robust Non-Parametric Template Matching with Local Rigidity Constraints." IEICE Transactions on Information and Systems E99.D, no. 9 (2016): 2332–40. http://dx.doi.org/10.1587/transinf.2015edp7492.

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5

Amit, Mika, Rolf Backofen, Steffen Heyne, Gad M. Landau, Mathias Mohl, Christina Otto, and Sebastian Will. "Local Exact Pattern Matching for Non-Fixed RNA Structures." IEEE/ACM Transactions on Computational Biology and Bioinformatics 11, no. 1 (January 2014): 219–30. http://dx.doi.org/10.1109/tcbb.2013.2297113.

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6

Zhong, Ying, Xue-zhi Yang, Yi-ming Tang, Can-jun Liu, and Feng Yue. "Non-local Means Denoising Derived from Structure-adapted Block Matching." Journal of Electronics & Information Technology 35, no. 12 (February 23, 2014): 2908–15. http://dx.doi.org/10.3724/sp.j.1146.2013.00099.

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7

Ying Luo, 罗颖, 霍冠英 Guanying Huo, 许金鑫 Jinxin Xu, and 李庆武 Qingwu Li. "Non-Local Stereo Matching Algorithm Based on Edge Constraint Iteration." Laser & Optoelectronics Progress 56, no. 15 (2019): 151501. http://dx.doi.org/10.3788/lop56.151501.

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8

Zahari, Madiha, Rostam Affendi Hamzah, Nurulfajar Abd Manap, and Adi Irwan Herman. "Stereo matching algorithm for autonomous vehicle navigation using integrated matching cost and non-local aggregation." Bulletin of Electrical Engineering and Informatics 12, no. 1 (February 1, 2023): 328–37. http://dx.doi.org/10.11591/eei.v12i1.4122.

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Stereo matching algorithm plays an important role in an autonomous vehicle navigation system to ensure accurate three-dimensional (3D) information is provided. The disparity map produced by the stereo matching algorithm directly impacts the quality of the 3D information provided to the navigation system. However, the accuracy of the matching algorithm is a challenging part to be solved since it is directly affected by the surrounding environment such as different brightness, less texture surface, and different image pair exposure. In this paper, a new framework of stereo matching algorithm that used the integration of census transform (CT) and sum of absolute difference (SAD) at the matching cost computation step, non-local cost aggregation at the second step, winner take all strategy at the third step, and a median filter at the final step to minimize disparity map error. The results show that the accuracy of the disparity map is improved using the proposed methods after some parameter adjustment. Based on the standard Middlebury and KITTI benchmarking dataset, it shows that the proposed framework produced accurate results compared with other established methods.

9

Li, Dongrui, Xiaofeng Huang, and Ying Yang. "Research on image denoising algorithm based on non-local block matching." International Journal of Information and Communication Technology 16, no. 3 (2020): 245. http://dx.doi.org/10.1504/ijict.2020.10027484.

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10

Yang, Ying, Dongrui Li, and Xiaofeng Huang. "Research on image denoising algorithm based on non-local block matching." International Journal of Information and Communication Technology 16, no. 3 (2020): 245. http://dx.doi.org/10.1504/ijict.2020.106317.

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Більше джерел

Дисертації з теми "Non-local matching":

1

Zhou, Dan. "Stereo Matching Based on Edge-Aware T-MST." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35538.

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Dense stereo matching is one of the most extensively investigated topics in computer vision, since it plays an important role in many applications such as 3D scene reconstruction. In this thesis, a novel dense stereo matching method is proposed based on edge-aware truncated minimum spanning tree (T-MST). Instead of employing non-local cost aggregation on traditional MST which is only generated from color differences of neighbouring pixels, a new tree structure, "Edge-Aware T-MST", is proposed to aggregate the cost according to the image texture. Specifically, cost aggregations are strongly enforced in large planar textureless regions due to the truncated edge weights. Meanwhile, the "edge fatten" effect is suppressed by employing a novel hybrid edge-prior which combines edge-prior and superpixel-prior to locate the potential disparity edges. Then a widely used Winner-Takes-All (WTA) strategy is performed to establish initial disparity map. An adaptive non-local refinement is also performed based on the stability of initial disparity estimation. Given the stereo images from Middlebury benchmark, we estimate the disparity maps by using our proposed method and other five state-of-the-art tree-based non-local matching methods. The experimental results show that the proposed method successfully produced reliable disparity values within large planar textureless regions and around object disparity boundaries. Performance comparisons demonstrate that our proposed non-local stereo matching method based on edge-aware T-MST outperforms current non-local tree-based state-of-the-art stereo matching methods in most cases, especially in large textureless planar regions and around disparity bounaries.

2

St-Jean, Samuel. "Acquisitions d'IRM de diffusion à haute résolution spatiale : nouvelles perspectives grâce au débruitage spatialement adaptatif et angulaire." Mémoire, Université de Sherbrooke, 2015. http://hdl.handle.net/11143/6993.

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Le début des années 2000 a vu la cartographie du génome humain se réaliser après 13 ans de recherche. Le défi du prochain siècle réside dans la construction du connectome humain, qui consiste à cartographier les connexions du cerveau en utilisant l’imagerie par résonance magnétique (IRM) de diffusion. Cette technique permet en effet d’étudier la matière blanche du cerveau de façon complètement non invasive. Bien que le défi soit monumental, la résolution d’une image d’IRM se situe à l’échelle macroscopique et est environ 1000 fois inférieure à la taille des axones qu’il faut cartographier. Pour aider à pallier à ce problème, ce mémoire propose une nouvelle technique de débruitage spécialement conçue pour l’imagerie de diffusion. L’algorithme Non Local Spatial and Angular Matching (NLSAM) se base sur les principes du block matching et du dictionary learning pour exploiter la redondance des données d’IRM de diffusion. Un seuillage sur les voisins angulaire est aussi réalisé à l’aide du sparse coding, où l’erreur de reconstruction en norme l2 est bornée par la variance locale du bruit. L’algorithme est aussi conçu pour gérer le biais du bruit Ricien et Chi non centré puisque les images d’IRM contiennent du bruit non Gaussien. Ceci permet ainsi d’acquérir des données d’IRM de diffusion à une plus grande résolution spatiale que présentement disponible en milieu clinique. Ce travail ouvre donc la voie à un meilleur type d’acquisition, ce qui pourrait contribuer à révéler de nouveaux détails anatomiques non discernables à la résolution spatiale présentement utilisée par la communauté d’IRM de diffusion. Ceci pourrait aussi éventuellement contribuer à identifier de nouveaux biomarqueurs permettant de comprendre les maladies dégénératives telles que la sclérose en plaques, la maladie d’Alzheimer et la maladie de Parkinson.

3

Carrillo, Hernan. "Colorisation d'images avec réseaux de neurones guidés par l'intéraction humaine." Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0016.

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La colorisation est le processus qui consiste à ajouter des couleurs aux images en niveaux de gris. C’est une tâche importante dans la communauté de l’édition d’images et de l’animation. Bien que des méthodes de colorisation automatique existent, elles produisent souvent des résultats insatisfaisants en raison de défauts tels que le débordement de couleur, l’incohérence, des couleurs non naturelles et la nature non trivial du problème. Par conséquent, une intervention manuelle est souvent nécessaire pour obtenir le résultat souhaité. En conséquence, il y a un intérêt croissant à automatiser le processus de colorisation tout en permettant aux artistes d’ajouter leur propre style et vision. Dans cette thèse, nous étudions divers formats d’interaction en guidant les couleurs sur des zones spécifiques d’une image, ou en les transférant à partir d’une image ou d’un objet de référence. Nous introduisons deux méthodes de colorisation semi-automatiques. Tout d’abord, nous décrivons une architecture d’apprentissage profond pour la colorisation d’images qui prend en compte les images de référence de l’utilisateur. Notre deuxième méthode utilise un modèle de diffusion pour coloriser des dessins en utilisant des indications de couleur fournies par l’utilisateur. Cette thèse commence par l’état de l’art des méthodes de colorisation d’images, des espaces de couleur, des métriques d’évaluation et des fonctions de perte. Bien que les méthodes de colorisation récentes basées sur des techniques d’apprentissage profond obtiennent les meilleurs résultats, ces méthodes sont basées sur des architectures complexes et un grand nombre de fonctions de perte, ce qui rend difficile leur compréhension. Pour cela, nous utilisons une architecture simple afin d’analyser l’impact de différents espaces de couleur et fonctions de perte. Ensuite, nous proposons une nouvelle couche d’attention appelée super-attention qui utilise des superpixels. Elle permet d’établir des correspondances entre les caractéristiques hautes résolutions de paires d’images cible et référence. Cette proposition permet d’atténuer le problème de la complexité quadratique des couches d’attention. De plus, elle aide à surmonter les défauts de débordement de couleur dans la tâche de colorisation. Nous étudions son utilisation pour le transfert de couleur, et pour la colorisation basée sur des exemples. Nous proposons également une extension de ce modèle afin de guider spécifiquement la colorisation sur des objets segmentés. Enfin, nous proposons un modèle de diffusion probabiliste basé sur des conditionnements implicites et explicites, pour apprendre à coloriser des dessins au trait. Notre approche permet d’ajouter des interactions utilisateur à travers des indices de couleur explicites tout en s’appuyant sur l’entraînement du modèle de diffusion principal. Nous utilisons un encodeur spécifique qui apprend à extraire des informations sur les indices de couleur fournis par l’utilisateur. Ce modèle permet d’obtenir des images colorisées diverses et de haute qualité
Colorization is the process of adding colors to grayscale images. It is an important task in the image-editing and animation community. Although automatic colorization methods exist, they often produce unsatisfying results due to artifacts such as color bleeding, inconsistency, unnatural colors, and the ill-posed nature of the problem. Manual intervention is often necessary to achieve the desired outcome. Consequently, there is a growing interest in automating the colorization process while allowing artists to transfer their own style and vision to the process. In this thesis, we investigate various interaction formats by guiding colors of specific areas of an image or transferring them from a reference image or object. As part of this research, we introduce two semi-automatic colorization frameworks. First, we describe a deep learning architecture for exemplar-based image colorization that takes into account user’s reference images. Our second framework uses a diffusion model to colorize line art using user-provided color scribbles. This thesis first delves into a comprehensive overview of state-of-the-art image colorization methods, color spaces, evaluation metrics, and losses. While recent colorization methods based on deep-learning techniques are achieving the best results on this task, these methods are based on complex architectures and a high number of joint losses, which makes the reasoning behind each of these methods difficult. Here, we leverage a simple architecture in order to analyze the impact of different color spaces and several losses. Then, we propose a novel attention layer based on superpixel features to establish robust correspondences between high-resolution deep features from target and reference image pairs, called super-attention. This proposal deals with the quadratic complexity problem of the non-local calculation in the attention layer. Additionally, it helps to overcome color bleeding artifacts. We study its use in color transfer and exemplar-based colorization. We finally extend this model to specifically guide the colorization on segmented objects. Finally, we propose a diffusion probabilistic model based on implicit and explicit conditioning mechanism, to learn colorizing line art. Our approach enables the incorporation of user guidance through explicit color hints while leveraging on the prior knowledge from the trained diffusion model. We condition with an application-specific encoder that learns to extract meaningful information on user-provided scribbles. The method generates diverse and high-quality colorized images

4

Romanenko, Ilya. "Novel image processing algorithms and methods for improving their robustness and operational performance." Thesis, Loughborough University, 2014. https://dspace.lboro.ac.uk/2134/16340.

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Image processing algorithms have developed rapidly in recent years. Imaging functions are becoming more common in electronic devices, demanding better image quality, and more robust image capture in challenging conditions. Increasingly more complicated algorithms are being developed in order to achieve better signal to noise characteristics, more accurate colours, and wider dynamic range, in order to approach the human visual system performance levels.

5

Giraud, Remi. "Algorithmes de correspondance et superpixels pour l’analyse et le traitement d’images." Thesis, Bordeaux, 2017. http://www.theses.fr/2017BORD0771/document.

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Cette thèse s’intéresse à diverses composantes du traitement et de l’analyse d’images par méthodes non locales. Ces méthodes sont basées sur la redondance d’information présente dans d’autres images, et utilisent des algorithmes de recherche de correspondance, généralement basés sur l’utilisation patchs, pour extraire et transférer de l’information depuis ces images d’exemples. Ces approches, largement utilisées par la communauté de vision par ordinateur, sont souvent limitées par le temps de calcul de l’algorithme de recherche, appliqué à chaque pixel, et par la nécessité d’effectuer un prétraitement ou un apprentissage pour utiliser de grandes bases de données.Pour pallier ces limites, nous proposons plusieurs méthodes générales, sans apprentissage,rapides, et qui peuvent être facilement adaptées à diverses applications de traitement et d’analyse d’images naturelles ou médicales. Nous introduisons un algorithme de recherche de correspondances permettant d’extraire rapidement des patchs d’une grande bibliothèque d’images 3D, que nous appliquons à la segmentation d’images médicales. Pour utiliser de façon similaire aux patchs,des présegmentations en superpixels réduisant le nombre d’éléments de l’image,nous présentons une nouvelle structure de voisinage de superpixels. Ce nouveau descripteur permet d’utiliser efficacement les superpixels dans des approches non locales. Nous proposons également une méthode de décomposition régulière et précise en superpixels. Nous montrons comment évaluer cette régularité de façon robuste, et que celle-ci est nécessaire pour obtenir de bonnes performances de recherche de correspondances basées sur les superpixels
This thesis focuses on several aspects of image analysis and processing with non local methods. These methods are based on the redundancy of information that occurs in other images, and use matching algorithms, that are usually patch-based, to extract and transfer information from the example data. These approaches are widely used by the computer vision community, and are generally limited by the computational time of the matching algorithm, applied at the pixel scale, and by the necessity to perform preprocessing or learning steps to use large databases. To address these issues, we propose several general methods, without learning, fast, and that can be easily applied to different image analysis and processing applications on natural and medical images. We introduce a matching algorithm that enables to quickly extract patches from a large library of 3D images, that we apply to medical image segmentation. To use a presegmentation into superpixels that reduces the number of image elements, in a way that is similar to patches, we present a new superpixel neighborhood structure. This novel descriptor enables to efficiently use superpixels in non local approaches. We also introduce an accurate and regular superpixel decomposition method. We show how to evaluate this regularity in a robust manner, and that this property is necessary to obtain good superpixel-based matching performances

6

Lin, Zong-Han, and 林宗翰. "The Study of Integrating Block Matching 3D and Non-Local Means Image Denoising Algorithms." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5650006%22.&searchmode=basic.

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碩士
國立中興大學
通訊工程研究所
107
Since digital images are often interfered by noises from various sources, image denoising is an important technique in image processing. Non-local means (NLM) algorithm achieves denoising through block matching. It compares the block of a pixel to be denoised with its neighboring blocks and uses the weighted average of all the neighboring pixels to remove noises. Later, block-matching 3D (BM3D) algorithm also uses the concept of block matching in image denoising. BM3D gathers similar blocks into a 3D group. It then uses collaborative filtering in these 3-D groups to remove noises. Collaborative filtering is accomplished in three steps: 1) 3D transformation of a group, 2) shrinkage of the transform coefficients, and 3) inverse 3D transformation. BM3D repeats the above block matching and collaborative filtering approach twice. In the first stage, hard thresholding is used in the shrinkage of the transform coefficients. In the second stage, Wiener filtering is used in the shrinkage. Therefore, there are three different denoising blocks from NLM and BM3D: a NLM denoising block, a BM3D denoising block in its first stage, and a BM3D denoising block in its second stage. By combining these three blocks in two steps, this thesis aims to find the best combination among the nine possibilities. Since the second stage of the BM3D require a reference with small noise interference, it cannot achieve acceptable denoising performance if put at the first step of the combination. Therefore, this thesis considers the other six combination by eliminating the second stage of BM3D from the first step of the combination. Experimental results demonstrate that NLM in the first step combined with the first stage of BM3D in the second step can speed up the processing by 2.98 times with only a small sacrifice in denoising performance.

7

Hsieh, Cheng-Hung, and 謝正宏. "A Non-Local Stereo Matching Algorithm Based on Improved Minimum Spanning Tree Structure and Occlusion Handling." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/6bn3ce.

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碩士
國立臺北科技大學
電機工程系所
102
The work proposed a non-local-based stereo matching algorithm for disparity computation. The feature of non-local stereo matching method is to utilize a tree structure to propagate weighted matching cost, and thus it can achieve both the merits of accuracy and speed in global and local methods respectively. In this work, a new minimum spanning tree forming method is proposed. Our method adopts 8-connected rather than 4-connected grid to construct the minimum spanning tree, and we also exploit the stereo matching cost as the confidence value, to prioritize tree built-up order from the increased connection possibilities of 8-connected grid. Compared to the original non-local stereo matching method in literature, our proposed tree built-up method significantly improves the error rate of disparity from 5.48 to 4.85 by the Middlebury benchmark. This work also proposed a multiple left-right consistency checking method to identify occlusion points efficiently for further refining their disparity. After applying it, our error rate is further decreased from 4.85 to 4.80, while the overall complexity of ours is only 1.24 times of the original non-local method.

Книги з теми "Non-local matching":

1

Identification of Local Matching Fund Requirements for State-Administered Federal and Non-Federal Public Transportation Programs. Washington, D.C.: National Academies Press, 2011. http://dx.doi.org/10.17226/14530.

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2

Horing, Norman J. Morgenstern. Retarded Green’s Functions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0005.

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Chapter 5 introduces single-particle retarded Green’s functions, which provide the probability amplitude that a particle created at (x, t) is later annihilated at (x′,t′). Partial Green’s functions, which represent the time development of one (or a few) state(s) that may be understood as localized but are in interaction with a continuum of states, are discussed and applied to chemisorption. Introductions are also made to the Dyson integral equation, T-matrix and the Dirac delta-function potential, with the latter applied to random impurity scattering. The retarded Green’s function in the presence of random impurity scattering is exhibited in the Born and self-consistent Born approximations, with application to Ando’s semi-elliptic density of states for the 2D Landau-quantized electron-impurity system. Important retarded Green’s functions and their methods of derivation are discussed. These include Green’s functions for electrons in magnetic fields in both three dimensions and two dimensions, also a Hamilton equation-of-motion method for the determination of Green’s functions with application to a 2D saddle potential in a time-dependent electric field. Moreover, separable Hamiltonians and their product Green’s functions are discussed with application to a one-dimensional superlattice in axial electric and magnetic fields. Green’s function matching/joining techniques are introduced and applied to spatially varying mass (heterostructures) and non-local electrostatics (surface plasmons).

Частини книг з теми "Non-local matching":

1

Clifford, Raphaël, and Benjamin Sach. "Online Approximate Matching with Non-local Distances." In Combinatorial Pattern Matching, 142–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02441-2_13.

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2

Landau, Gad M., Avivit Levy, and Ilan Newman. "LCS Approximation via Embedding into Local Non-repetitive Strings." In Combinatorial Pattern Matching, 92–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02441-2_9.

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3

Amit, Mika, Rolf Backofen, Steffen Heyne, Gad M. Landau, Mathias Möhl, Christina Schmiedl, and Sebastian Will. "Local Exact Pattern Matching for Non-fixed RNA Structures." In Combinatorial Pattern Matching, 306–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31265-6_25.

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4

Sankoff, David. "Edit distance for genome comparison based on non-local operations." In Combinatorial Pattern Matching, 121–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-56024-6_10.

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5

Nguyen, Hong Phuc, Thi Dinh Tran, and Quang Vinh Dinh. "Local Stereo Matching by Joining Shiftable Window and Non-parametric Transform." In Lecture Notes in Computer Science, 133–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35455-7_13.

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6

Du, Jianning, Yanbing Xue, Hua Zhang, and Zan Gao. "Stereo Matching Based on Density Segmentation and Non-Local Cost Aggregation." In Advances in Multimedia Information Processing – PCM 2018, 253–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00767-6_24.

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Iguernaissi, Rabah, Djamal Merad, and Pierre Drap. "People’s Re-identification Across Multiple Non-overlapping Cameras by Local Discriminative Patch Matching." In Lecture Notes in Computer Science, 190–97. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59876-5_22.

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Chen, Geng, Yafeng Wu, Dinggang Shen, and Pew-Thian Yap. "XQ-NLM: Denoising Diffusion MRI Data via x-q Space Non-local Patch Matching." In Lecture Notes in Computer Science, 587–95. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46726-9_68.

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9

Tsai, Chun-Jen, and Aggelos K. Katsaggelos. "Dense Disparity Estimation via Global and Local Matching." In Noblesse Workshop on Non-Linear Model Based Image Analysis, 289–94. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1597-7_45.

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Xu, Jinxin, Xueling Yang, Jinbo Zuo, Jiayan Mu, and Zhiqiang Guan. "Forward-Backward Diffusion and Pruning-Based Cost Aggregation for Non-Local Stereo Matching." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde221021.

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Minimum spanning tree (MST) has been devised for non-local cost aggregation to solve the stereo matching problem. However, the cost aggregation is employed directly from leaf toward root node, then in an inverse pass without considering any decision rules. And a small amount of noise is also existed in stereo image pairs. Both of the limitations often lead to failure in achieving more competitive results. This paper presents a novel stereo matching algorithm using forward-backward diffusion and pruning-based cost aggregation. In “forward-backward” process, the raw image pairs are smoothened on a horizontal tree structure as well as retaining image edges sharp. During cost aggregation, the MST where a complete graph involves the whole image pixels is cut off self-adaptively when the depth edge information is referred to. Each node in this tree receives supports from all other nodes which belong to similar depth regions. Meanwhile, an enhanced edge similarity function between two nearest neighboring nodes is formulated to deal with the small-weight-accumulation problem in textureless regions. Consequently, the cost volume can be well aggregated. The proposed method is demonstrated on Middlebury v.2 & v.3 datasets and can obtain good performance in disparity accuracy compared with other five MST based stereo matching methods.

Тези доповідей конференцій з теми "Non-local matching":

1

Koster, Urs, and Aapo Hyvarinen. "Natural image statistics: Energy-based models estimated by score matching." In 2009 International Workshop on Local and Non-Local Approximation in Image Processing (LNLA 2009). IEEE, 2009. http://dx.doi.org/10.1109/lnla.2009.5278409.

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2

Xu, Juan, Zhihui Wei, and Yubao Sun. "Non-Local Means Image Denoising with Local Geometric Structures Matching Strategy." In 2009 2nd International Congress on Image and Signal Processing (CISP). IEEE, 2009. http://dx.doi.org/10.1109/cisp.2009.5301368.

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3

Gould, S. "Multiclass pixel labeling with non-local matching constraints." In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2012. http://dx.doi.org/10.1109/cvpr.2012.6248002.

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4

Qingxiong Yang. "A non-local cost aggregation method for stereo matching." In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2012. http://dx.doi.org/10.1109/cvpr.2012.6247827.

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5

Huang, Xiaoming, Guoqin Cui, and Yundong Zhang. "A fast non-local disparity refinement method for stereo matching." In 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014. http://dx.doi.org/10.1109/icip.2014.7025776.

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Zhou, Ziheng, Samuel Chindaro, and Farzin Deravi. "Non-linear fusion of local matching scores for face verification." In Gesture Recognition (FG). IEEE, 2008. http://dx.doi.org/10.1109/afgr.2008.4813338.

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Altantawy, Doaa A., Marwa Obbaya, and Sherif Kishk. "A fast non-local based stereo matching algorithm using graph cuts." In 2014 9th International Conference on Computer Engineering & Systems (ICCES). IEEE, 2014. http://dx.doi.org/10.1109/icces.2014.7030943.

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Carrillo, Hernan, Michaël Clément, and Aurélie Bugeau. "Non-local Matching of Superpixel-based Deep Features for Color Transfer." In 17th International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0010767900003124.

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9

Ma, Yong, Huabing Zhou, Jun Chen, Jingshu Shi, and Zhongyuan Wang. "Non-rigid feature matching for image retrieval using global and local regularizations." In 2017 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2017. http://dx.doi.org/10.1109/icme.2017.8019441.

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Zhong, Heng, Yahu Zhu, and Deqi Ming. "An efficient stereo matching method based on non-local spatial tree filter." In ICCIR 2022: 2022 2nd International Conference on Control and Intelligent Robot. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3548608.3559180.

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Звіти організацій з теми "Non-local matching":

1

van den Boogaard,, Vanessa, and Fabrizio Santoro. Co-Financing Community-Driven Development Through Informal Taxation: Experimental Evidence from South-Central Somalia. Institute of Development Studies (IDS), September 2021. http://dx.doi.org/10.19088/ictd.2021.016.

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Community contributions are often required as part of community-driven development (CDD) programmes, with payment encouraged through matching grants. However, little remains known about the impact of matching grants, or the implications of requiring community contributions in order for communities to receive development funding. This paper describes research where we partner with two non-governmental organisations (NGOs) – one international and one Somali – and undertake a randomised control trial of a CDD matching grant programme designed to incentivise informal contributions for local public goods in Gedo region in south-central Somalia. We rely on household survey data collected from 1,297 respondents in 31 treatment and 31 control communities, as well as surveys of village leaders and data on informal contributions from the mobile money platform used by community leaders to collect revenue. Two key findings emerge. First, our research shows that working with communities and incentivising informal revenue generation can be an effective way to deliver public goods and to support citizens and communities. Second, building on research exploring the potential for development interventions to spur virtuous or adverse cycles of governance, we show that development partners may work directly with community leaders and informal taxing institutions without necessarily undermining – and indeed perhaps strengthening – state legitimacy and related ongoing processes of statebuilding in the country. Indeed, despite playing no direct role in the matching grant programme, taxpayer perceptions of the legitimacy of the local government improved as a result of the programme. These findings deepen our understanding of how community contributions may be incentivised through matching grant programmes, and how they may contribute to CDD and public goods provision in a context of weak institutional capacity.

2

Bleakley, Hoyt, and Kevin Cowan. Corporate Dollar Debt and Depreciations: Much Ado about Nothing? Inter-American Development Bank, July 2005. http://dx.doi.org/10.18235/0010842.

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Much has been written recently about the problems for emerging markets that might result from a mismatch between foreign-currency denominated liabilities and assets (or income flows) denominated in local currency. In particular, several models, developed in the aftermath of financial crises of the late 1990s, suggest that the expansion in the "peso" value of "dollar" liabilities resulting from a devaluation could, via a net worth effect, offset the expansionary competitiveness effect. Assessing which effect dominates is ultimately an empirical matter. In this vein, this paper constructs a new database with accounting information (including the currency composition of liabilities) for over 450 non-financial firms in five Latin American countries. The authors estimate, at the firm level, the reduced-form effect on investment of holding foreign-currency-denominated debt during an exchange-rate realignment. It is consistently found that, contrary to the predicted sign of the net-worth effect, firms holding more dollar debt do not invest less than their counterparts in the aftermath of a depreciation. The paper shows that this result is due to firms matching the currency denomination of their liabilities with the exchange-rate sensitivity of their profits. Because of this matching, the negative balance-sheet effects of a depreciation on firms holding dollar debt are offset by the larger competitiveness gains of these firms.

3

Raei, Lamia. Exploring the Links: Youth participation and employment opportunities in Jordan. Oxfam IBIS, August 2021. http://dx.doi.org/10.21201/2021.7981.

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Oxfam partners with the Jordanian Hashemite Fund for Human Development (JOHUD) through its Youth Participation and Employment (YPE) programme in order to connect with communities and train local community-based organizations (CBOs). JOHUD’s aim is to build the job-seeking capacity of youth in four governorates in Jordan. The programme organizes informal activities involving peer-to-peer education to help young people engage in the community as volunteers, and links them to various governmental and non-governmental institutions. COVID-19 and the associated lockdowns have altered the organization’s operations, with most projects shifting online. JOHUD has adopted a youth-led initiative aimed at matching young people’s skills with labour-market demand in each governorate where the programme operates. This case study presents examples of how the programme has helped young people transform into professionals, and how youth-led employment centres can contribute to youth development activities.

4

Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2015. http://dx.doi.org/10.55274/r0010891.

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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform lighting conditions. In the second part of the framework, the context-based segmentation is developed to eliminate regions from imagery that are not considered to be a threat to the pipeline. Context based segmentation makes use of a cascade of pre-trained classifiers to search for regions that are not threats. The context based segmentation algorithm accelerates threat identification and improves object detection rates. The last phase of the framework is an efficient object detection model. Efficient object detection �follows a three-stage approach which includes extraction of the local phase in the image and the use of local phase characteristics to locate machinery threats. The local phase is an image feature extraction technique which partially removes the lighting variance and preserves the edge information of the object. Multiple orientations of the same object are matched and the correct orientation is selected using feature matching by histogram of local phase in a multi-scale framework. The classifier outputs locations of threats to pipeline.�The advanced automatic image analysis system is intended to be capable of detecting construction equipment along the ROW of pipelines with a very high degree of accuracy in comparison with manual threat identification by a human analyst. �