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ICSOC '04: Proceedings of the Second International Conference on Service Oriented computing

作者： Sandholm, Thomas Gardfjäll, Peter Elmroth, Erik Johnsson, Lennart Mulmo, Olle Dept. of Numerical Analysis and Computer Science PDC Royal Institute of Technology SE-100 44 Stockholm Sweden Dept. of Computing Science and HPC2N Umeå University SE-901 87 Umeå Sweden Dept. of Computer Science Texas Learning and Computation Center University of Houston Houston TX 77204 United States

ISBN: (纸本)1581138717

In this paper, we present an Open Grid Services Architecture (OGSA)-based decentralized allocation enforcement system, developed with an emphasis on a consistent data model and easy integration into existing scheduling, and workload management software at six independent high-performance computing centers forming a Grid known as SweGrid. The Swedish National Allocations Committee (SNAC) allocates resource quotas at these centers to research projects requiring substantial computer time. Our system, the SweGrid Accounting System (SGAS), addresses the need for soft real-time allocation enforcement on SweGrid for cross-domain job submission. The SGAS framework is based on state-of-the-art Web and Grid services technologies. The openness and ubiquity of Web services combined with the fine-grained resource control and cross-organizational security models of Grid services proved to be a perfect match for the SweGrid needs. Extensibility and customizability of policy implementations for the three different parties the system serves (the user, the resource manager, and the allocation authority) are key design goals. Another goal is end-to-end security and single sign-on, to allow resources - selected based on client policies - to act on behalf of the user when negotiating contracts with the bank in an environment where the six centers would continue to use their existing accounting policies and tools. We conclude this paper by showing the feasibility of SGAS, which is currently being deployed at the production sites, using simulations of reservation streams. The reservation streams are shaped using soft computing and policy-based algorithms. Copyright 2004 ACM.

关键词： Computer science

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Velocity adaptation of space-time interest points

Velocity adaptation of space-time interest points

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International Conference on Pattern Recognition

作者： I. Laptev T. Lindeberg Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computer Science KTH Royal Institute of Technology Stockholm Sweden

The notion of local features in space-time has recently been proposed to capture and describe local events in video. When computing space-time descriptors, however, the result may strongly depend on the relative motion between the object and the camera. To compensate for this variation, we present a method that automatically adapts the features to the local velocity of the image pattern and, hence, results in a video representation that is stable with respect to different amounts of camera motion. Experimentally we show that the use of velocity adaptation substantially increases the repeatability of interest points as well as the stability of their associated descriptors. Moreover, for an application to human action recognition we demonstrate how velocity-adapted features enable recognition of human actions in situations with unknown camera motion and complex, non-stationary backgrounds.

关键词： Cameras Humans Image motion analysis Pattern recognition Motion measurement Optical recording Covariance matrix Computer vision Laboratories numerical analysis

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Recognizing human actions: a local SVM approach

Recognizing human actions: a local SVM approach

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International Conference on Pattern Recognition

作者： C. Schuldt I. Laptev B. Caputo Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper, we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition. For the purpose of evaluation we introduce a new video database containing 2391 sequences of six human actions performed by 25 people in four different scenarios. The presented results of action recognition justify the proposed method and demonstrate its advantage compared to other relative approaches for action recognition.

关键词： Humans Support vector machines Computer vision Pattern recognition Support vector machine classification Cameras Frequency Spatial databases Performance evaluation Image recognition

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Galilean-diagonalized spatio-temporal interest operators

Galilean-diagonalized spatio-temporal interest operators

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International Conference on Pattern Recognition

作者： T. Lindeberg A. Akbarzadeh I. Laptev Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computer Science KTH Royal Institute of Technology Stockholm Sweden

This paper presents a set of image operators for detecting regions in space-time where interesting events occur. To define such regions of interest, we compute a spatio-temporal second-moment matrix from a spatio-temporal scale-space representation, and diagonalize this matrix locally, using a local Galilean transformation in space-time, optionally combined with a spatial rotation, so as to make the Galilean invariant degrees of freedom explicit. From the Galilean-diagonalized descriptor so obtained, we then formulate different types of space-time interest operators, and illustrate their properties on different types of image sequences.

关键词： Cameras Covariance matrix Computer vision Laboratories numerical analysis Computer science Image sequences Layout Councils Filters

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Navigation for human-robot interaction tasks

Navigation for human-robot interaction tasks

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IEEE International Conference on Robotics and Automation (ICRA)

作者： P. Althaus H. Ishiguro T. Kanda T. Miyashita H.I. Christensen Centre for Autonomous Systems Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden ATR Intelligent Robotics and Communication Laboratories Keihanna Science City Kyoto Japan

One major design goal in human-robot interaction is that the robots behave in an intelligent manner, preferably in a similar way as humans. This constraint must also be taken into consideration when the navigation system for the platform is developed. However, research in human-robot interaction is often restricted to other components of the system including gestures, manipulation, and speech. On the other hand, research for mobile robot navigation focuses primarily on the task of reaching a certain goal point in an environment. We believe that these two problems can not be treated separately for a personal robot that coexists with humans in the same surrounding. Persons move constantly while they are interacting with each other. Hence, also a robot should do that, which poses constraints on the navigation system. This type of navigation is the focus of this paper. Methods have been developed for a robot to join a group of people engaged in a conversation. Preliminary results show that the platform's moving patterns are very similar to the ones of the persons. Moreover, this dynamic interaction has been judged naturally by the test subjects, which greatly increases the perceived intelligence of the robot.

关键词： Navigation Intelligent robots Human robot interaction Mobile robots Indoor environments numerical analysis Computer science Cities and towns Testing

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Multi-agent reinforcement learning: using macro actions to learn a mating task

Multi-agent reinforcement learning: using macro actions to l...

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2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)

作者： S. Elfwing E. Uchibe K. Doya H.I. Christensen CREST Japan Science and Technology Agency Kyoto Japan Centre for Autonomous Systems Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden Neural Computation Project Initial Research Project Okinawa Institute of Science and Technology Gushikawa Okinawa Japan Department of Computational Neurobiology ATR Computational Neuroscience Laboratories Japan

Standard reinforcement learning methods are inefficient and often inadequate for learning cooperative multi-agent tasks. For these kinds of tasks the behavior of one agent strongly depends on dynamic interaction with other agents, not only with the interaction with a static environment as in standard reinforcement learning. The success of the learning is therefore coupled to the agents' ability to predict the other agents behaviors. In this study we try to overcome this problem by adding a few simple macro actions, actions that are extended in time for more than one time step. The macro actions improve the learning by making search of the state space more effective and thereby making the behavior more predictable for the other agent. In this study we have considered a cooperative mating task, which is the first step towards our aim to perform embodied evolution, where the evolutionary selection process is an integrated part of the task. We show, in simulation and hardware, that in the case of learning without macro actions, the agents fail to learn a meaningful behavior. In contrast, for the learning with macro action the agents learn a good mating behavior in reasonable time, in both simulation and hardware.

关键词： Learning Hardware Robot kinematics Game theory Stochastic processes numerical analysis Computer science Genetic algorithms Animals Testing

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Pose-based clustering in action sequences

Pose-based clustering in action sequences

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IEEE International Workshop on Higher-Level Knowledge in 3D Modeling and Motion analysis (HLK)

作者： G. Loy J. Sullivan S. Carlsson Numerical Analysis and Computing Science Royal Institute of Technology Stockholm Sweden

A method is presented for automatically extracting key frames from an image sequence. The sequence is divided into clusters of frames with similar appearance, and the most central frame in each cluster defines a key frame. Clustering is done using an extension of the normalized cut segmentation technique based on the inter-frame similarities. The similarity between every pair of frames in the sequence is determined from the spatial image characteristics via a shape matching technique. Our algorithm is demonstrated successfully extracting 20 key frames for a tennis player in action over a 30 second (900 frame) video sequence.

关键词： Video sequences Humans Time measurement Image recognition numerical analysis Image sequences Image segmentation Shape Clustering algorithms Motion pictures

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Computational high frequency wave propagation

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Acta Numerica 2003年 12卷 181-266页

作者： Engquist, Björn Runborg, Olof PACM Department of Mathematics Princeton University Princeton NJ 08544 United States Department of Numerical Analysis and Computer Science Royal Institute of Technology (KTH) 10044 Stockholm Sweden

numerical simulation of high frequency acoustic, elastic or electro-magnetic wave propagation is important in many applications. Recently the traditional techniques of ray tracing based on geometrical optics have been augmented by numerical procedures based on partial differential equations. Direct simulations of solutions to the eikonal equation have been used in seismology, and lately approximations of the Liouville or Vlasov equation formulations of geometrical optics have generated impressive results. There are basically two techniques that follow from this latter approach: one is wave front methods and the other moment methods. We shall develop these methods in some detail after a brief review of more traditional algorithms for simulating high frequency wave propagation. © Cambridge University Press, 2003.

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Carving Prior Manifolds Using Inequalities

Carving Prior Manifolds Using Inequalities

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Martin Eriksson Stefan Carlsson Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden

The use of prior information by learning from training data is used increasingly in image analysis and computer vision. The high dimensionality of the parameter spaces and the complexity of the probability distributions however often makes the exact learning of priors an impossible problem, requiring an excessive amount of training data that is seldom realizable in practise. In this paper we propose a weaker form of prior estimation which tries to learn the boundaries of impossible events from examples. This is equivalent to estimating the support of the prior distribution or the manifold of possible events. The idea is to model the set of possible events by algebraic inequalities. Learning proceeds by selecting those inequalities that show a consistent sign when applied to the training data set. Every such inequality "carves" out a region of impossible events in the parameter space. The manifold of possible events estimated in this way will in general represent the qualitative properties of the events. We give example of this in the problems of restoration of handwritten characters and automatically tracked body locations

关键词： Shape Manifolds Training Smoothing methods Humans Bayesian methods Training data

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Three-query PCPs with perfect completeness over non-Boolean domains

Three-query PCPs with perfect completeness over non-Boolean ...

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Annual IEEE Conference on Computational Complexity

作者： L. Engebretsen J. Holmerin Department of Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden

We study nonBoolean PCPs that have perfect completeness and read three positions from the proof. For the case when the proof consists of values from a domain of size d for some integer constant d/spl ges/2, we construct a nonadaptive PCP with perfect completeness and soundness d/sup -1/+d/sup -2/+/spl epsiv/, for any constant /spl epsiv/>0, and an adaptive PCP with perfect completeness and soundness d/sup -1/+/spl epsiv/, for any constant /spl epsiv/>0. The latter PCP can be converted into a nonadaptive PCP with perfect completeness and soundness d/sup -1/+/spl epsiv/, for any constant /spl epsiv/>0, where four positions are read from the proof. These results match the best known constructions for the case d=2 and our proofs also show that the particular predicates we use in our PCPs are nonapproximable beyond the random assignment threshold.

关键词： Polynomials numerical analysis Computer science

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