Abstract: We study $H(\mathrm {div})$ preconditioning for the saddle-point systems that arise in a stochastic Galerkin mixed formulation of the steady-state diffusion problem with random data. The key ingredie...
Abstract: We study $H(\mathrm {div})$ preconditioning for the saddle-point systems that arise in a stochastic Galerkin mixed formulation of the steady-state diffusion problem with random data. The key ingredient is a multigrid V-cycle for an $H(\mathrm {div})$ operator with random weight function acting on a certain tensor product space of random fields with finite variance. We build on the Arnold-Falk-Winther multigrid algorithm presented in 1997 by varying the spatial discretization from grid to grid whilst keeping the stochastic discretization fixed. We extend the deterministic analysis to accommodate the modified $H(\mathrm {div})$ operator and establish spectral equivalence bounds with a new multigrid V-cycle operator that are independent of the spatial and stochastic discretization parameters. We implement multigrid within a block-diagonal preconditioner for the full saddle-point problem, derive eigenvalue bounds for the preconditioned system matrices and investigate the impact of all the discretization parameters on the convergence rate of preconditioned minres.
Kernel-based tracker shows robust performances in various object tracking technologies. Due to its robustness and accuracy, Kernel-based tracker using Mean-shift algorithm is regarded as one of the best ways to apply ...
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In this paper, a finger pose estimation method is presented. A direct use of fingers is useful in some applications which require handling of 3D position information. Our finger pose estimation method exploits anatomi...
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In this paper, a finger pose estimation method is presented. A direct use of fingers is useful in some applications which require handling of 3D position information. Our finger pose estimation method exploits anatomical constraints on finger motion and ring-shaped markers to achieve simple and practical measurements applicable to daily life situations. The use of anatomical constraints ensures that no exact placement of the markers is required.
AAAI was pleased to present the AAAI-08 Workshop program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers;AI Education Work...
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This article summarizes collaborative educational activities and joint educational program development between the computerscience department and other departments at the same and other institutions. We hope that thi...
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ISBN:
(纸本)9781605584157
This article summarizes collaborative educational activities and joint educational program development between the computerscience department and other departments at the same and other institutions. We hope that this article will aid Universities, Colleges and academia in achieving success in developing joint projects. The authors discuss the inter-institutional challenges of developing and deploying shared courses, and the benefits and challenges of new course development. Additionally, the paper describes the goals and results of three joint projects between Okanagan College (OC) and Vancouver Island University (VIU, formerly Malaspina University-College, BC, Canada), and presents information about the Nation-wide GIS Project in Lithuania, which was conducted by the VIU to develop national Spatial Data Infrastructure. Two of the four projects, mentioned above were developed for Okanagan College, while the third is the BC Campus Project: "Post Graduate Technical Diploma in GIS at the Malaspina University-College (lead), University of British Columbia (UBC), and Okanagan College" for the Vancouver Island University (VIU). Copyright 2009 ACM.
Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The ...
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ISBN:
(纸本)9781424420582
Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The proposed method reduces computational cost and has good performance. The experimental result shows that the proposed method not only runs faster but provides accurate result.
A foundational and highly contested question in cognitive science is whether and to what degree the brain is a modular system. This talk outlines some of the broad architectural implications of the modularity thesis, ...
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Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The ...
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ISBN:
(纸本)9781424420575
Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The proposed method reduces computational cost and has good performance. The experimental result shows that the proposed method not only runs faster but provides accurate result.
Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in ...
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Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in object-tracking technology in computer vision fields. However, it has a drawback of getting into a bottleneck state when faced with a speedy object moving beyond its window size within one image frame interval time. The time required to calculate mean-shift vector could be much lessened with lesser memory when color model is adjusted to the previously known target information. This paper shows the building process of target-adjusted model with a non-uniform quantization. The target color model dealt in this paper is the one used for deriving mean-shift vector. It is a kernel model containing both the color and distance information. This paper gives scheme to efficiently deal with color information in the model. Through a proper selection of color bins, unimportant color values were reduced to a small amount. As a result, the computing time of the mean-shift vector in face-tracking was shortened while maintaining robustness and accuracy.
In this paper, a simple method is proposed to evolve artificial neural networks(ANNs) using augmenting weight matrix method(AWMM). ANNs' architecture and connection weights can be evolved simultaneously by AWMM, a...
In this paper, a simple method is proposed to evolve artificial neural networks(ANNs) using augmenting weight matrix method(AWMM). ANNs' architecture and connection weights can be evolved simultaneously by AWMM, and their structures incrementally are growing up from minimal structure. It is a non-mating method. It employs 5 mutation operators: add connection, add node, delete connection, delete node, and new initial weight. And the connection weight is trained by the simplified alopex method, which is a correlation based method for solving optimization problem. In AWMM, structural information is encoded to weighting matrix, and the matrix is augmenting as the hidden nodes are added.
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