Curve matching plays a significant role in object recognition, target tracking and fragment reassembling. This paper presents a representation and matching algorithm for planar curve based on sub-matrix and concentric...
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Curve matching plays a significant role in object recognition, target tracking and fragment reassembling. This paper presents a representation and matching algorithm for planar curve based on sub-matrix and concentric circles. The algorithm includes two steps, namely rough matching and exact matching. The rough matching uses a sub-matrix matching method. As for exact matching, first, the representation of curve uses concentric circles and then measures their similarity through two curve representation sets of concentric circles. Our algorithm which is robust to the translation, rotation and scaling, can be used to match block objects and SAR image registration. The experiment results show us the effectiveness and feasibility of algorithm.
Humans are capable of identifying a book only by looking at its cover, but how can computers do the same? In this paper, we explore different feature detectors and matching methods for book cover identification, and c...
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ISBN:
(纸本)9781728122205
Humans are capable of identifying a book only by looking at its cover, but how can computers do the same? In this paper, we explore different feature detectors and matching methods for book cover identification, and compare their performances in terms of both speed and accuracy. This will allow, for example, libraries to develop interactive services based on cover book picture. Only one single image of a cover book needs to be available through a database. Tests have been performed by taking into account different transformations of each book cover image. Encouraging results have been achieved.
Internet-based matching markets have gained great attention during the last decade, such as Internet advertising (matching keywords and advertisers), ridesharing platforms (pairing riders and drivers), crowdsourcing m...
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Internet-based matching markets have gained great attention during the last decade, such as Internet advertising (matching keywords and advertisers), ridesharing platforms (pairing riders and drivers), crowdsourcing markets (assigning tasks to workers), online dating (pairing romantically attracted partners), etc. A fundamental challenge is the presence of uncertainty, which manifests in the following two ways. The first is on the arrival of agents in the system, e.g., drivers and riders in ridesharing services, keywords in the Internet advertising, and online workers in crowdsourcing markets. The second is on the outcome of interaction. For example, two users may like or dislike each other after a dating arranged by a match-making firm, a user may click or not click the link of an advertisement shown by an Ad company, to name a few. We are now living in an era of big data, fortunately. Thus, by applying powerful machine learning techniques to huge volumes of historical data, we can often get very accurate estimates of the uncertainty in the system as described above. Given this, the question then is as follows: How can we exploit estimates for our benefits as a matching-policy designer? This dissertation aims to address this question. We have built an AI toolbox, which takes as input the estimates over uncertainty in the system, appropriate objectives (e.g., maximization of the total profit, maximization of fairness, etc.), and outputs a matching policy which works well both theoretically and experimentally on those pre-specified targets. The key ingredients are two matching models: stochastic matching and online matching. We have made several foundational algorithmic progress for these two models. Additionally, we have successfully utilized these two models to harness estimates from powerful machine learning algorithms, and designed improved matching policies for various real matching markets including ridesharing, crowdsourcing, and online recommendation applicat
The calculation of matches between pixels, points, or other features in stereo images is known as the correspondence problem. This problem is ill-posed due to occlusions;not every pixel, point or feature in one stereo...
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The calculation of matches between pixels, points, or other features in stereo images is known as the correspondence problem. This problem is ill-posed due to occlusions;not every pixel, point or feature in one stereo image has a match in the other. Minimization of a cost function over some local region and dynamic programming algorithms are two well-known strategies for computing dense correspondences. However the former approach fails in regions of low texture, while the latter imposes an ordering constraint which is not always satisfied in stereo images. In this study, we present two new techniques for computing dense stereo correspondence. The new methods are based on combinatorial optimization techniques which require polynomial computation time. The first method casts the selection of matches as the assignment problem, solved efficiently by finding a maximum weighted matching on a bipartite graph. The second is a greedy algorithm which computes suboptimal weighted matchings on the bipartite graphs. Both methods use occlusion nodes when no matches exist. The resulting disparity maps have desirable properties such as dense correspondence, while avoiding the drawbacks associated with ordering constraints. Three existing matching approaches are also reviewed for comparative purposes. We test all five techniques on real and synthetic stereo images using performance criteria which specifically measure occlusion detection. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Despite the efforts of the international biometric community, the measurement of the accuracy of a biometric system is far from being completely investigated and, eventually, standardized. This paper presents a critic...
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Despite the efforts of the international biometric community, the measurement of the accuracy of a biometric system is far from being completely investigated and, eventually, standardized. This paper presents a critical analysis of the accuracy and performance measurement of a biometric system. Current approaches to the problem and procedural error have been described and criticized. Finally, a methodology for the measurement of the accuracy of biometric systems with nonsymmetric matching function will be proposed and discussed.
With the development of computing technology, the storage space and computing power of IoT devices have developed rapidly. Due to the social nature of people, users who have social relationships with each other IoT de...
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With the development of computing technology, the storage space and computing power of IoT devices have developed rapidly. Due to the social nature of people, users who have social relationships with each other IoT devices are relatively close in some time periods, but are far away from traditional edge nodes. It is far away, so service providers can temporarily rent suitable IoT devices to act as edge storage nodes based on the storage computing power and social status of user equipment. In the process of selecting edge nodes by service providers, this paper firstly describes the social relationships of users to which the edge nodes belong and some requirements for storage. Then, based on the above considerations, a method based on social and The edge node selection algorithm of equipment storage, and the subsequent modeling of the problem of service providers' selection of edge nodes as the problem of maximizing social benefits, through the use of matching algorithms, proves that the algorithm proposed in this paper can effectively select edge nodes, and subsequent simulation experiments The experimental results also show that the proposed algorithm can maximize the social benefits of service providers and users.
In many application fields (e.g., aerospace and biomedical image processing), one has to deal with a sequence of images whose observation is made difficult by unpredictable relative movements of the camera and the sce...
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In many application fields (e.g., aerospace and biomedical image processing), one has to deal with a sequence of images whose observation is made difficult by unpredictable relative movements of the camera and the scene. In order to obtain a stable display, the displacement of each image in the sequence with respect to one chosen as a reference must be preliminarily determined. This would usually require two-dimensional algorithms, involving a considerable computational effort. This work discusses a new algorithm for image registration, which requires only one-dimensional Fourier transformations. Preliminary experimental results are reported.
Consider a forest that evolves via link operations that make the root of one tree the child of a node in another tree. Intermixed with link operations are nca operations, which return the nearest common ancestor of tw...
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Consider a forest that evolves via link operations that make the root of one tree the child of a node in another tree. Intermixed with link operations are nca operations, which return the nearest common ancestor of two given nodes when such exists. This article shows that a sequence of m such nca and link operations on a forest of n nodes can be processed online in time O(m alpha(m, n) + n). This was previously known only for a restricted type of link operation. The special case where a link only extends a tree by adding a new leaf occurs in Edmonds' algorithm for finding a maximum weight matching on a general graph. Incorporating our algorithm into the implementation of Edmonds' algorithm in [9] achieves time O(n(m + n logn)) for weighted matching, an arguably optimum asymptotic bound (n and m are the number of vertices and edges, respectively). Our data structure also provides a simple alternative implementation of the incremental-tree set merging algorithm of Gabow and Tarjan [11].
The Double Traveling Salesman Problem with Multiple Stacks, DTSPMS, deals with the collect and delivery of n commodities in two distinct cities, where the pickup and the delivery tours are related by LIFO constraints....
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The Double Traveling Salesman Problem with Multiple Stacks, DTSPMS, deals with the collect and delivery of n commodities in two distinct cities, where the pickup and the delivery tours are related by LIFO constraints. During the pickup tour, commodities are loaded into a container of k rows, or stacks, with capacity c. This paper focuses on computational aspects of the DTSPMS, which is NP-hard. We first review the complexity of two critical subproblems: deciding whether a given pair of pickup and delivery tours is feasible and, given a loading plan, finding an optimal pair of pickup and delivery tours, are both polynomial under some conditions on k and c. We then prove a (3k)/2 standard approximation for the Min Metric k DTSPMS, where k is a universal constant, and other approximation results for various versions of the problem. We finally present a matching-based heuristic for the 2DTSPMS, which is a special case with k = 2 rows, when the distances are symmetric. This yields a 1/2 - o(1), 3/4 - o(1) and 3/2 + o(1) standard approximation for respectively Max2DTSPMS, its restriction Max2DTSPMS(1,2) with distances 1 and 2, and Min2DTSPMS(1,2), and a 1/2 - o(1) differential approximation for Min2DTSPMS and Max2DTSPMS. (C) 2021 Elsevier B.V. All rights reserved.
Anytime, anywhere social computing requires several support mechanisms and tools, including location and proximity systems, expressive representation models of physical place and user characteristics, and effective so...
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Anytime, anywhere social computing requires several support mechanisms and tools, including location and proximity systems, expressive representation models of physical place and user characteristics, and effective social-matching algorithms. Anytime, anywhere social-network computing also requires shared and interoperable vocabularies for modeling location and entity characteristics. Current solutions tend to address only a subset of these issues. We believe that the success of anytime, anywhere social computing depends on middleware solutions that separate social-network management concerns from application requirements. Our middleware solution, the socially aware and mobile architecture (SAMOA), integrates a set of common management facilities for personalizing location-dependent social networks, and for propagating social networks' visibility up to the application level.
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