In the studying of fibers microstructure of brain white matter,many reconstruction methods have been proposed to interpret the diffusion-weighted signalThose methods can be categorized into modelbased and model-free m...
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In the studying of fibers microstructure of brain white matter,many reconstruction methods have been proposed to interpret the diffusion-weighted signalThose methods can be categorized into modelbased and model-free methodsIn this paper,the diffusion configuration of water molecules are discussed,and two questions are put forward to analyze the performance of the current algorithms about diffusion configuration.
Graph matching (GM) is a fundamental problem in computer science, and it has been successfully applied to provide solutions to many problems in computer vision. In this paper, we consider GM as a clustering problem in...
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ISBN:
(纸本)9781479939046
Graph matching (GM) is a fundamental problem in computer science, and it has been successfully applied to provide solutions to many problems in computer vision. In this paper, we consider GM as a clustering problem in an association graph whose nodes represent candidate correspondences between two graphs to be matched. And we take the dense subgraph as a good prior for correct correspondences, thus we propose a label propagation approach to expand the dense subgraph to resolve the whole cluster. The label propagation approach is achieved by an affinity-preserving manifold ranking algorithm with a dynamic label vector which enforces the matching constraints. And the matching constraints is introduced through a doubly-stochastic normalization procedure. Extensive experiments demonstrate that our algorithm outperforms the state-of-the-art GM algorithms especially in the presence of outliers and deformation.
An objective approach is proposed to measure the image degradation caused by optical transmission effects of atmospheric turbulence. Comparisons of the proposed measure with existing objective image quality measures a...
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ISBN:
(纸本)9781479954599
An objective approach is proposed to measure the image degradation caused by optical transmission effects of atmospheric turbulence. Comparisons of the proposed measure with existing objective image quality measures are performed and the correlations between the measure and subjective ratings are quantified. Experiments on wind-tunnel images and simulated turbulence-degraded images produce good results. The proposed measure may serve as a complement to state-of-the-art measures in evaluating image degradation caused by turbulence. It can also be applied as a criterion for frame selection and iteration termination for iterative restoration algorithms or help evaluate the performances of image restoration algorithms.
In this paper, a novel and robust tracking method based on efficient manifold ranking is proposed. For tracking, tracked results are taken as labeled nodes while candidate samples are taken as unlabeled nodes, and the...
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In this paper, a novel and robust tracking method based on efficient manifold ranking is proposed. For tracking, tracked results are taken as labeled nodes while candidate samples are taken as unlabeled nodes, and the goal of tracking is to search the unlabeled sample that is the most relevant with existing labeled nodes by manifold ranking algorithm. Meanwhile, we adopt non-adaptive random projections to preserve the structure of original image space, and a very sparse measurement matrix is used to efficiently extract low-dimensional compressive features for object representation. Furthermore, spatial context is used to improve the robustness to appearance variations. Experimental results on some challenging video sequences show the proposed algorithm outperforms six state-of-the-art methods in terms of accuracy and robustness.
Mapping RDB to RDF (i.e., RDB2RDF) is the key to constructing the Semantic Web, hence has been an active research field during the last decade. Many technically heterogeneous RDB2RDF tools resulted in non-interchangea...
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Mapping RDB to RDF (i.e., RDB2RDF) is the key to constructing the Semantic Web, hence has been an active research field during the last decade. Many technically heterogeneous RDB2RDF tools resulted in non-interchangeable and unreusable RDB2RDF mapping descriptions. In 2009, the W3C RDB2RDF Incubator Group Report once strongly suggested that the RDB2RDF mapping language be expressed in rules as defined by the W3C Rule Interchange Format (RIF) Working Group, because rules are an effective way to express mappings between information models, and RIF, as part of the infrastructure for the Semantic Web, is now a standard for exchanging rules among Web rule systems. This paper addresses the issue of RIF-based RDB2RDF mapping and proposes a database semantics-driven, RIF Production Rule Dialect (RIF-PRD) based mapping description approach. The work includes defining a set of generic RIF-PRD mapping rules for RDB2RDF, developing a prototype mapping engine called RIFD2RME (stands for RIF-based RDB2RDF Mapping Engine), and conducting case study experiments with the prototype. The experimental results indicate that the proposed mapping approach is achievable and effective.
The skeleton of an image object is a simplified representation, which is of great significance for the imagerecognition and matching. To obtain a smooth and accurate skeleton of a specified object in the gray image, ...
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The main drawback of conventional filtering based methods for small dim target (SDT) detection is they could not guarantee sufficient suppression ability towards trivial high frequency component which belongs to backg...
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ISBN:
(纸本)9781479928941
The main drawback of conventional filtering based methods for small dim target (SDT) detection is they could not guarantee sufficient suppression ability towards trivial high frequency component which belongs to background, such as strong corners and edges. To overcome this bottleneck, this paper proposes an effective SDT detection algorithm by using local connectedness constraint. Our method provides direct control for target size, ensure high accuracy and could be easily embedded into the classical sliding-window based framework. The effectiveness of the proposed method is validated using images with cluttered background.
It is a challenging task to develop an effective and robust visual tracking method due to factors such as pose variation, illumination change, occlusion, and motion blur. In this paper, a novel tracking algorithm base...
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ISBN:
(纸本)9781479957521
It is a challenging task to develop an effective and robust visual tracking method due to factors such as pose variation, illumination change, occlusion, and motion blur. In this paper, a novel tracking algorithm based on weighted subspace reconstruction error is proposed. We first compute the discriminative weights by sparse construction error with template dictionary consisted of positive and negative samples, and then confidence map for candidates is computed through subspace reconstruction error. Finally, the location of the target object is estimated by maximizing the decision map which is combined discriminative weights and subspace reconstruction error. Furthermore, we use the new evaluation criterion to verify the robustness of the current tracking result, which can reduce the accumulated error effectively. Experimental results on some challenging video sequences show that the proposed algorithm performs favorably against seven state-of-the-art methods in terms of accuracy and robustness.
Automatically assessment of photo quality in different categories is of great interest in the recent years. And there are many researches work on it. In this paper, we use several new global and regional features to d...
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Automatically assessment of photo quality in different categories is of great interest in the recent years. And there are many researches work on it. In this paper, we use several new global and regional features to describe the photo quality. In one image, there is an area where attract the most attention of humans eyes. We call this area subject area. We use two different methods to extract the subject area while dealing with different kinds of images. Then we extract the regional feature from the subject area and background separately. Photos taken by professional photographer have obvious difference between subject area and background. We combine global features and regional features, and our method performs quite well in the database.
Automatic image annotation is an attractive service for users and administrators of online photo sharing websites. In this paper, we propose an image annotation approach exploiting visual and textual saliency. For tex...
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