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检索条件"任意字段=Conference on Visualization and Data Analysis 2011"

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Global contrast based salient region detection

Global contrast based salient region detection

引用

conference on Computer Vision and Pattern Recognition (CVPR)

作者： Ming-Ming Cheng Guo-Xin Zhang Niloy J. Mitra Xiaolei Huang Shi-Min Hu TNList Tsinghua University China KAUST Saudi Arabia Lehigh University USA

Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their contents, and thus remains an important step in many computer vision tasks including image segmentation, object recognition, and adaptive compression. We propose a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence. The proposed algorithm is simple, efficient, and yields full resolution saliency maps. Our algorithm consistently outperformed existing saliency detection methods, yielding higher precision and better recall rates, when evaluated using one of the largest publicly available data sets. We also demonstrate how the extracted saliency map can be used to create high quality segmentation masks for subsequent image processing.

关键词： Image color analysis Image segmentation Quantization visualization Smoothing methods Histograms Humans

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Assessment of the market power cost in liberalised electricity markets using SMPI, PMPI, and NMPI indicators

Assessment of the market power cost in liberalised electrici...

引用

International conference on European Electricity Market, EEM

作者： M. R. Hesamzadeh M. Amelin School of Electrical Engineering Royal Institute of Technology Stockholm Sweden

Market power analysis is one of the major issues facing regulators of wholesale electricity markets. The exercise of market power both distorts wholesale price signals and reduces the efficiency of the operation of and investment in the wholesale electricity market. This paper deals with a systematic way for quantifying and visualising market power. The paper first proposes three indicators termed the System Market Power Indicator, SMPI, the Producer Market Power Indicator, PMPI, and the Nodal Market Power Indicator, NMPI. The game theory in applied mathematics and the concept of social welfare in microeconomics are used in formulating of these indicators. The SMPI finds the total cost of exercising market power by generating companies. The contribution of a specific generating company in system market power is calculated using the PMPI. The NMPI finds the contribution of each power system node in the total market power cost. Then after, a colour contour map is used to visualise the exercise of market power and its associated cost. The proposed market power indicators are applied to the modified Garver's example system to show the promising performance of these indicators.

关键词： Generators Electricity supply industry Companies Biological system modeling data visualization Economics Electricity

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Unscented information filter based multi-sensor data fusion using stereo camera, laser range finder and GPS receiver for vehicle localization

Unscented information filter based multi-sensor data fusion ...

引用

International conference on Intelligent Transportation

作者： Lijun Wei Cindy Cappelle Yassine Ruichek Laboratoire Systèmes et Transports Universitè de Technologie de Belfort-Montbèliard Belfort France

An Unscented Information Filter (UIF) based multi-sensor fusion method for ground vehicles localization in urban environments is presented and evaluated. UIF is used to fuse information acquired from a stereo vision system, a laser range finder and a GPS receiver in order to provide more robust vehicle localization results. Stereovision based visual odometry is used as input of the UIF prediction stage. By the analysis of stereo images, the relative motion is estimated after removing the tracking outliers. Then, laser range finder based positions and GPS readouts are used as measurements to update the information state vector after consistency validation. Besides, a MICP (modified iterative closest points) method is proposed to ameliorate the performance of laser scan alignment by applying dynamic distance error threshold. The obtained results demonstrate that the MICP method reduces the matching ambiguities of the classic ICP method. The proposed multi-sensor localization method was tested with real data and was evaluated using RTK-GPS as the ground truth. It shows that the UIF based method provides accurate localization services during GPS outages (e.g., GPS jumps, GPS mask), while avoiding the trajectory drift of stereo camera and laser range finder based methods.

关键词： Global Positioning System Vehicles Cameras Vectors visualization Iterative closest point algorithm Receivers

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Simulating situational awareness with User-Defined Operating Picture (UDOP) devices using rules

Simulating situational awareness with User-Defined Operating...

引用

IEEE International Multi-Disciplinary conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA)

作者： James M. Niehaus Scott Neal Reilly Charles River Analytics 슠Inc. Cambridge MA USA

The Network-Centric Warfare paradigm provides Ground Soldiers in the U.S. Army with large amounts of information needed to maintain situational awareness and perform successfully in the field. Current information interfaces lack a targeted operational focus and provide a broad superset of data, which results in Ground Soldiers becoming overloaded by extraneous or non-critical information. To address this issue, the U.S. Army is developing User-Defined Operational Picture (UDOP) technology that manages incoming information to maximize Soldier effectiveness. However, many simulation-based analysis tools do not currently provide a means of modeling UDOPs and their effect on Soldier performance, and new modeling and simulation technologies are needed to address this gap. This work presents a method for modeling and simulation of simulated Soldier situational awareness in a constructive simulation based on simulated UDOP capability and known limits of human information processing. We present the modeling of UDOP capability and Soldier decision making through rules, and discuss the advantages and disadvantages of this approach, including verification and validation, computational performance, transition to operational UDOP devices, and ease of modeling.

关键词： Computational modeling visualization Analytical models Syntactics Fires Weapons Atmospheric modeling

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Detection and analysis of Trend Topics for Global Scientific Literature Using Feature Selection Based on Gini-Index

Detection and Analysis of Trend Topics for Global Scientific...

引用

International conference on Tools for Artificial Intelligence (ICTAI)

作者： Heum Park Eunsun Kim Kuk-Jin Bae Hyuk Hahn Tae-Eung Sung Hyuk-Chul Kwon Center of U-Port IT Research and Education Pusan National University Busan South Korea Korea Institute of Science Technology Information Seoul South Korea School of Computer Science and Engineering Pusan National University Busan South Korea

As the volume and diversity of scientific resources grows, trend detection and analysis have become much more important issues. A variety of trend detection, characterization, evaluation and visualization methodologies have been introduced for various application domains. In this paper, we consider detection of temporal trends for topics using feature selection and extraction of additional information from the subtopics of them, for the Global Trends Briefing (GTB) dataset. Thus, we propose a novel trend detection method using feature selection based on the Improved Gini-Index (I-GI) algorithm, which can obtain representative features for given topics. Second, with those features, we extract subtopics for the topics and visualize temporal/emerging/upward/ downward trends with them. Third, utilizing the relations among the subtopics, we obtain relevant documents and seed sentences that co-occur with the upper features for the topic. In addition, we can extract information to forecast future trends relevant to the issues: for example, financial market or emerging technology. In the experimental results, we could obtain good representative features, more specific trends for the topics, and additional useful information.

关键词： Feature extraction Fuel cells Classification algorithms data mining Light emitting diodes Smart grids Batteries

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Driving me around the bend: Learning to drive from visual gist

Driving me around the bend: Learning to drive from visual gi...

引用

International conference on Computer Vision Workshops (ICCV Workshops)

作者： Nicolas Pugeault Richard Bowden Centre of Vision Speech and Signal Processing University of Surrey UK

This article proposes an approach to learning steering and road following behaviour from a human driver using holistic visual features. We use a random forest (RF) to regress a mapping between these features and the driver's actions, and propose an alternative to classical random forest regression based on the Medoid (RF-Medoid), that reduces the underestimation of extreme control values. We compare prediction performance using different holistic visual descriptors: GIST, Channel-GIST (C-GIST) and Pyramidal-HOG (P-HOG). The proposed methods are evaluated on two different datasets: predicting human behaviour on countryside roads and also for autonomous control of a robot on an indoor track. We show that 1) C-GIST leads to the best predictions on both sequences, and 2) RF-Medoid leads to a better estimation of extreme values, where a classical RF tends to under-steer. We use around 10% of the data for training and show excellent generalization over a dataset of thousands of images. Importantly, we do not engineer the solution but instead use machine learning to automatically identify the relationship between visual features and behaviour, providing an efficient, generic solution to autonomous control.

关键词： visualization Roads Vegetation Vehicles Vectors Training Regression tree analysis

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Using Takagi-Sugeno-Kang approximation fuzzy logic for evaluating the performance of color difference formulas in dentistry

Using Takagi-Sugeno-Kang approximation fuzzy logic for evalu...

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International conference on Intelligent Systems Design and Applications (ISDA)

作者： Razvan Ghinea Juan de la Cruz Cardona Ana María Ionescu María del Mar Perez Luis Javier Herrera Department of Optics Faculty of Science University of Granada Granada Spain Department of Computer Architecture and Computer Technology E.T.S.I.I.T. University of Granada Granada Spain

The present work carries out a novel study on the determination of color acceptability thresholds using a Takagi-Sugeno-Kang (TSK) fuzzy approximation, performing an evaluation of the CIEDE2000(K L :K C :K H ) color difference formula in dentistry. A total of 55 sample pairs were evaluated by a panel of 28 observers. The responses for each pair were processed, and data was fitted using a TSK Fuzzy Approximation, which in recent literature has proven to be a reliable and recommendable methodology for approximating color data in dentistry. 50:50% acceptability thresholds were calculated for both CIEDE2000(1:1:1) and CIEDE2000(2:1:1) formulas and the performance of these formulas was evaluated using the PF/3 and STRESS parameters. We obtained better values for all performance parameters for CIEDE2000(2:1:1), indicating the better agreement between this formula and the visual results. Our results suggest considering reviewing the parametric factors, so that the CIEDE2000 color difference formula can be properly used for further applications in dentistry.

关键词： Image color analysis Dentistry Approximation methods visualization Observers Stress Fitting

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AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video

AVSS 2011 demo session: A large-scale benchmark dataset for ...

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IEEE conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Sangmin Oh Anthony Hoogs Amitha Perera Naresh Cuntoor Chia-Chih Chen Jong Taek Lee Saurajit Mukherjee J. K. Aggarwal Hyungtae Lee Larry Davis Eran Swears Xiaoyang Wang Qiang Ji Kishore Reddy Mubarak Shah Carl Vondrick Hamed Pirsiavash Deva Ramanan Jenny Yuen Antonio Torralba Bi Song Anesco Fong Amit Roy-Chowdhury Mita Desai Sabanci University Istanbul Turkey

Summary form only given. We present a concept for automatic construction site monitoring by taking into account 4D information (3D over time), that is acquired from highly-overlapping digital aerial images. On the one hand today's maturity of flying micro aerial vehicles (MAVs) enables a low-cost and an efficient image acquisition of high-quality data that maps construction sites entirely from many varying viewpoints. On the other hand, due to low-noise sensors and high redundancy in the image data, recent developments in 3D reconstruction workflows have benefited the automatic computation of accurate and dense 3D scene information. Having both an inexpensive high-quality image acquisition and an efficient 3D analysis workflow enables monitoring, documentation and visualization of observed sites over time with short intervals. Relating acquired 4D site observations, composed of color, texture, geometry over time, largely supports automated methods toward full scene understanding, the acquisition of both the change and the construction site's progress.

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Novelty detection using growing neural gas for visuo-spatial memory

Novelty detection using growing neural gas for visuo-spatial...

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2011 IEEE/RSJ International conference on Intelligent Robots and Systems

作者： Dmitry Kit Brian Sullivan Dana Ballard Computer Sciences University of Texas at Austin Austin TX USA Psychology University of Texas at Austin Austin TX USA

Detecting visual changes in environments is an important computation with many applications in robotics and computer vision. Security cameras, remotely operated vehicles, and sentry robots could all benefit from robust change detection capability. We conjecture that if one has a mobile camera system the number of visual scenes that are experienced is limited (compared to the space of all possible scenes) and that the scenes do not frequently undergo major changes between observations. These assumptions can be exploited to ease the task of change detection and reduce the computational complexity of processing visual information by utilizing memory to store previous computations. We demonstrate a method to learn the distribution of visual features in an environment via a self-organizing map. Additionally, the spatial distribution of these features can be learned if a positional signal is available. Our method uses a low dimensional representation of visual features to rapidly detect changes in current visual inputs. The model encodes spatially-distributed color histograms of real world visual scenes captured by a camera moved through an environment. The distribution of the color histograms is learned using a self-organizing map with location (when available) and color data. We present tests of the model on detecting changes in an indoor environment.

关键词： Histograms visualization Image color analysis Cameras Training Robots Vectors

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Harmonic propagation analysis in electric energy distribution systems

Harmonic propagation analysis in electric energy distributio...

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International conference on Electrical Power Quality and Utilisation (EPQU)

作者： L. C. O. Oliveira G. A. e Melo J. B. Souza C. A. Canesin B. D. Bonatto F. N. Belchior M. Oliveira E. A. Mertens São Paulo State University Ilha Solteira Sao Paulo Brazil Elektro Electricity and Services Company Brazil Federal University of Itajuba Brazil

An important alteration of the equivalent loads profile has been observed in the electrical energy distribution systems, for the last years. Such fact is due to the significant increment of the electronic processors of electric energy that, in general, behave as nonlinear loads, generating harmonic distortions in the currents and voltages along the electric network. The effects of these nonlinear loads, even if they are concentrated in specific sections of the network, are present along the branch circuits, affecting the behavior of the entire electric network. For the evaluation of this phenomenon it is necessary the analysis of the harmonic currents flow and the understanding of the causes and effects of the consequent voltage harmonic distortions. The usual tools for calculation the harmonic flow consider one-line equivalent networks, balanced and symmetrical systems. Therefore, they are not tools appropriate for analysis of the operation and the influence/interaction of mitigation elements. In this context, this work proposes the development of a computational tool for the analysis of the three-phase harmonic propagation using Norton modified models and considering the real nature of unbalanced electric systems operation.

关键词： Harmonic analysis Load modeling Harmonic distortion data visualization Current measurement Voltage measurement Computational modeling

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