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

作者： F.J. Estrada A.D. Jepson Centre for Vision Research York University Toronto ONT Canada Department of Comp. Science University of Toronto Toronto ONT Canada

This paper presents a perceptual grouping algorithm that performs boundary extraction on natural images. Our grouping method maintains and updates a model of the appearance of the image regions on either side of a growing contour. This model is used to change grouping behaviour at run-time, so that, in addition to following the traditional Gestalt grouping principles of proximity and good continuation, the grouping procedure favours the path that best separates two visually distinct parts of the image. The resulting algorithm is computationally efficient and robust to clutter and texture. We present experimental results on natural images from the Berkeley Segmentation Database and compare our results to those obtained with three alternate grouping methods.

关键词： Robustness change detection algorithms Runtime Image segmentation Image databases Visual databases Humans Data mining Parallel processing Educational institutions

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Genesis: A Scalable Self-Evolving Performance Management Framework for Storage Systems

Genesis: A Scalable Self-Evolving Performance Management Fra...

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International Conference on Distributed Computing Systems

作者： K.T. Pollack S.M. Uttamchandani University of California Santa Cruz USA Almaden Research Center IBM USA

data-center environment, the administrator needs to understand the root-cause of the issue. The growing trend of system virtualization, combined with the need to support end-to-end performance goals for enterprise applications, have made root-cause analysis a nontrivial problem - administrators are required to manually parse all hardware events, configuration modifications, and changes in access characteristics, across all tiers of the IO path from application servers to the disks. We propose a framework that assists storage administrators with root-cause analysis in distributed systems. GENESIS consists of three key modules: Abnormality detection, Snapshot Generation, and Diagnosis. The Abnormality detection module uses clustering algorithms to create and constantly evolve the normality models of measurable parameters in components. The Snapshot Generator is triggered by a combination of abnormality detection and policies to take compact snapshots of the system state for analysis whenever a significant change occurs. The Diagnosis module parses the snapshots and shortlists the root-cause for the administrator using knowledge about the impact of the run-time changes on IO performance. We have implemented an initial proof-of-concept of GENESIS in GPFS (a high performance distributed file-system) and validated its operation for several interesting real-world scenarios. Encouraged by the results, we are currently deploying our prototype in an existing data center environment.

关键词： Performance analysis Runtime Transaction databases Delay Switches History Environmental management Application virtualization Hardware change detection algorithms

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Gateway Subset Difference Revocation

Gateway Subset Difference Revocation

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Jeffrey Opper Brian DeCleene May Leung BAE Systems Advanced Information Technologies Burlington MA USA

Subset difference revocation (SDR) provides a powerful mechanism for the efficient expression of the revocation state of a large group of key recipients. However, arbitrary assignment of receivers as leaf nodes in a static binary tree can lead to inefficiencies in certain group revocation states. Gateway subset difference revocation (GSDR), developed in our ongoing SecureKeys effort, provides the ability to group receivers based upon organizational characteristics while simultaneously introducing the ability to audit rekey and data transmission, delegate rekey decisions to subordinate decision makers, and override subordinate rekey authority when necessary. GSDR extends the existing SDR scheme by deploying rekey gateways in a hierarchy that mimics an organic decision making structure. Delegation of rekey authority offloads a significant computational and communications burden from gateways high in the tree, while correspondingly partitioning the rekey traffic required to be processed by leaf nodes in the tree. GSDR also significantly reduces label storage requirements in rekey devices by limiting terminal node fan-out

关键词： Partitioning algorithms Information technology change detection algorithms Receivers Cryptography Proposals Binary trees Data communication Decision making Radio communication

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Fragment packet partial re-assembly method for intrusion detection

Fragment packet partial re-assembly method for intrusion det...

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International Conference on Advanced Communication Technology (ICACT)

作者： Bo-Heung Chung Jae-Deok Lim Seung-Ho Ryu Young-Ho Kim Ki-Young Kim Electronics and Telecommnications Research Institute South Korea

This paper proposes the fragment packet partial re-assembly method for intrusion detection. In the proposed method, intrusion detection is performed not with all the fragment packets but with partial fragment packets. If the fragment packet comes, the packet-matching-buffer containing the partial part of the previous fragment packet and this packet is merged into a packet-matching-buffer. After this work, pattern matching for this buffer is done. Finally, for the purpose of the next packet, the partial region of the current packet is stored into the packet-matching-buffer. With the help of these steps, there are two advantages. The one is that it doesn't need to re-assemble all fragment packets for intrusion detection. The other is that the size of buffer can be smaller than all fragment packet re-assembly and can be predictable as a constant size. The proposed method can be used efficiently to prevent malicious code of attackers for avoiding intrusion detection system

关键词： Intrusion detection Pattern matching Assembly change detection algorithms Buffer storage Merging Delay

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In-Network Outlier detection in Wireless Sensor Networks

In-Network Outlier Detection in Wireless Sensor Networks

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International Conference on Distributed Computing Systems

作者： J. Branch B. Szymanski C. Giannella Ran Wolff H. Kargupta Computer Science Rensselaer Polytechnic Institute NY USA Computer Science & Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an algorithm that (1) is flexible with respect to the outlier definition, (2) works in-network with a communication load proportional to the outcome, and (3) reveals its outcome to all sensors. We examine the algorithm’s performance using simulation with real sensor data streams. Our results demonstrate that the algorithm is accurate and imposes a reasonable communication load and level of power consumption.

关键词： Intelligent networks Wireless sensor networks Data analysis change detection algorithms Computer science Energy consumption Robustness Pattern analysis Distributed computing Neural networks

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Design and Evaluation of a Fast and Robust Worm detection Algorithm

Design and Evaluation of a Fast and Robust Worm Detection Al...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： T. Bu A. Chen S. Vander Wiel T. Woo Bell Laboratories Lucent Technologies Inc. USA Los Alamos National Laboratory USA

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change detection of enhanced, no-changed and reduced scattering in multi-temporal ERS-2 SARimages using the two-thresholds EM and MRF algorithms

Change detection of enhanced, no-changed and reduced scatter...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ya-Qiu Jin Key Laboratory of Wave Scattering and Remote Sensing Information Ministry of Education Fudan University Shanghai China

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A Time-Consistent Video Segmentation Algorithm designed for Real-Time Implementation

A Time-Consistent Video Segmentation Algorithm designed for ...

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13th IEEE International Conference on Electronics, Circuits and Systems (ICECS'2006), vol.2

作者： Mohammed El Hassani Delphine Rivasseau Stephanie Jehan-Besson Marinette Revenu Luc Brun David Tschumperle Marc Duranton Laboratoire Systèmes et Transports Université de Technologie de Belfort-Montbliard (UTBM) Belfort France Department of Electrical Engineering and Information Systems University of Tokyo Tokyo Japan FEMTO-ST/FCLab UMR CNRS 6174 Université de Technologie de Belfort-Montbliard (UTBM) Belfort France Westside Gotanda B1F Alnair Labs Corporation Tokyo Japan Laboratory GREYC Caen University France Philips Research Eindhoven Netherlands

In this paper, we propose a time consistent video segmentation algorithm designed for real-time implementation. Our segmentation algorithm is based on a region merging process that combines both spatial and motion information. The spatial segmentation takes benefit of an adaptive decision rule and a specific order of merging. Our method has proven to be efficient for the segmentation of natural images (¤at or textured regions) with few parameters to be set Temporal consistency of the segmentation is ensured by incorporating motion information through the use of an improved change detection mask. This mask is designed using both illumination differences between frames, and region segmentation of the previous frame. By considering both pixel and region levels, we obtain a particularly efficient algorithm at a low computational cost, allowing its implementation in real-time on the TriMedia processor for CIF image sequences.

关键词： Algorithm design and analysis Image segmentation Merging Motion detection Motion estimation Laboratories Pixel change detection algorithms Computational efficiency Image sequences

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Track-before-detect procedures for early detection of moving target from airborne radars

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2005年第3期41卷 937-954页

作者： Buzzi, S Lops, M Venturino, L Università degli Studi di Cassino Italy

In this paper we present a family of track-before-detect (TBD). procedures for early detection of moving targets from airborne radars. Upon a sectorization of the coverage area, the received echoes are jointly processed in the azimuth-range-Doppler domain and in the time domain through a Viterbi-like algorithm that exploits the physically admissible target transitions between successive illuminations, in order to collect all of the energy back-scattered during the time on target (TOT). A reduced-complexity implementation is derived assuming, at the design stage, that the target does not change resolution cell during the TOT in each scan. The constant false alarm rate (CFAR) constraint is also englobed in the proposed procedures as well as the possibility of working with quantized data. Simulation results show that the proposed algorithms have good detection and tracking capabilities even for high target velocities and low quantization rates.

关键词： Radar tracking Target tracking Radar detection Airborne radar Optical filters Laser radar Optical sensors Radar applications change detection algorithms Object detection

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A novel approach to change detection based on a coarse-to-fine strategy

A novel approach to change detection based on a coarse-to-fi...

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IEEE International Conference on Image Processing

作者： A. Bevilacqua L. Di Stefano A. Lanza G. Capelli Department of Electronics Computer Science and Systems (DEIS) Advanced Research Centre .Ercole De Castro. (ARCES) University of Bologna Bologna Italy

We present a novel approach to the change detection problem based on a coarse-to-fine strategy. The basic idea consists in assigning to an efficient preliminary coarse-level detection the task to filter out the well known possible false changes (e.g., those due to camera noise and small displacements, or to scene illumination changes). This provides the subsequent fine-level detection with reliable supermasks of the true changed areas in the scene. In this way, the fine-level detection can "focus the attention" on limited parts of the frames, thus yielding remarkable advantages in terms of computational efficiency. Here, just a coarse-level detection algorithm based on background subtraction and on the concept of structure is presented, to stress that any pixel-level algorithm can be used afterwards and benefit in terms of robustness as well as of computational efficiency.

关键词： Cameras Layout Lighting detection algorithms change detection algorithms Event detection Noise robustness Computer science Stress Computer vision

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