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IEEE International conference on Multimedia and Expo (ICME)

作者： Shih-Hung Lee C.H. Yeh C.-C. Jay Kuo Integrated Media Systems Center and Department of Electrical Engineering University of Southern California Los Angeles CA USA

A skimming system for movie content exploration is proposed using story units extracted via general tempo analysis of audio and visual data. Quite a few schemes have been proposed to segment video data into shots with low-level features, yet the grouping of shots into meaningful units, called story units here, is important and challenging. In this work, we detect similar shots using keyframes and include these similar shots as a node. Then, an importance measure is calculated based on the total length of each node. Finally, we select sinks and shots according to this measure. Based on these semantic shots, a meaningful skim can be successfully generated. Simulation results are presented to show that the proposed video skimming scheme can preserve the essential and significant content of the original video data

关键词： Motion pictures Length measurement Event detection Gunshot detection systems data mining Modems Explosions Motion analysis Motion detection Rhythm

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Panel 2: In the Eye of the Beholder: The Role of Perception in Scientific visualization 04

Panel 2: In the Eye of the Beholder: The Role of Perception ...

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Proceedings of the conference on visualization '04

作者： David Ebert Bill Geisler David Laidlaw Kelly Gaither Purdue University University of Texas at Austin Brown University

ISBN: (纸本)9780780387881

The evolution of computational science over the last decade has resulted in a dramatic increase in raw problem solving capabilities. This growth has given rise to advances in scientific and engineering simulations that have put a high demand on tools for high-performance large-scale data exploration and analysis. These simulations have the potential to generate large amounts of data. Humans, however are relatively poor at gaining insight from raw numerical data, and as a result, have used visualization as a tool for understanding, interpreting and exploring data of all types and sizes. Allowing for efficient visual explorations of data, however, requires that the ratio of knowledge gained versus the cost of the visualization be maximized. This, in turn, mandates the integration of principles from human perception. Understanding perception as it relates to visualization requires that we understand not only the biology of the human visual system, but principles from vision theory, and perceptual psychology as well. This panel is the result of bringing together practioners and researchers from a broad spectrum of interests relating to the ability to maximize the amount of information that is effectively perceived from a given visualization. Position statements will be given by researchers interested in perceptual psychology and the perception of natural images, integrating art and design principles, non-photorealistic rendering techniques, and the use of global illumination methods to provide benefical perceptual cues.

关键词： human visual system

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Interpreting fuzzy clustering results with virtual reality-based visual data mining: Application to microarray gene expression data

Interpreting fuzzy clustering results with virtual reality-b...

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conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： J.J. Valdes National Research Council Canada Ottawa ONT Canada

This paper combines fuzzy clustering with a virtual reality based technique for visual data mining. The purpose is to construct virtual reality spaces preserving as much structural information from the original data as possible, where the results of fuzzy clustering procedures can be displayed and analyzed. The construction of such spaces involves non-linear transformations of the original feature space, which can be either the space of the original attributes or the space of the fuzzy memberships with respect to the constructed fuzzy classes. In particular, the representation involves the centroids of the different classes, the individual memberships of all of the studied objects with respect to all of the fuzzy classes, and eventually their comparison with additional crisp partitions or partitions induced by a decision attribute. This approach is applied to different data sets from the fields of biology and medicine, including microarray gene expression data related to Alzheimer's disease and Leukemia. The visual inspection and the navigation in the virtual reality spaces, provided useful insights about (i) the quality of the obtained classifications, (ii) the overlapping of different classes, and (iii) their relationships.

关键词： data mining Gene expression Virtual reality Navigation data analysis data structures Councils Information technology Space technology Information analysis

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Panel 2: In the Eye of the Beholder: The Role of Perception in Scientific visualization

Panel 2: In the Eye of the Beholder: The Role of Perception ...

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IEEE conference on visualization

作者： K. Gaither D. Ebert B. Geisler D. Laidlaw University of Texas at Austin Purdue University USA Brown University USA

关键词： data visualization Humans Computational modeling Psychology Evolution (biology) Problem-solving data engineering Analytical models Large-scale systems data analysis

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PET-SORTEO: a platform for simulating realistic PET studies

PET-SORTEO: a platform for simulating realistic PET studies

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： A. Reilhac G. Batan C. Michel N. Costes A.C. Evans McConnell Brain Imaging Centre Montreal Neurological Institute and Hospital Montreal QUE Canada CPS-PET System Knoxville TN USA Centre d''Exploration et de Recherche Médicales par Emission de Positons Lyon France

We present here the features and validation results of a Monte Carlo-based PET simulation platform designed to address the increasing need of simulated studies. The simulation tool, named PET-SORTEO, includes i) the generation of the raw projections in accordance with both the numerical phantom description as well as with the scanner geometry and physical characteristics, and ii) the correction and reconstruction of the raw data. Validation results show that the platform reliably reproduces the image formation processes and includes correctly the sources of noise and biases

关键词： Positron emission tomography Solid modeling Character generation Image reconstruction Computational modeling Imaging phantoms Interference Geometry Reconstruction algorithms data analysis

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Terrain classification through weakly-structured vehicle/terrain interaction

Terrain classification through weakly-structured vehicle/ter...

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IEEE International conference on Robotics and Automation (ICRA)

作者： A.C. Larson R.M. Voyles G.K. Demir Department of Computer Science University of Minnesota Minneapolis MN Department of Computer Science University of Minnesota Minneapolis MN USA Department of Electrical and Electronics Engineering Dokuz Eylul University Izmir Turkey

We present a new terrain classification technique both for effective, autonomous locomotion over natural, unknown terrains and for the qualitative analysis of terrains for exploration and mapping. Our straight-forward approach requires a single camera with little processing of visual information. Specifically, we derived a gait bounce measure from visual servoing errors that result from vehicle-terrain interactions during normal locomotion. Characteristics of the terrain, such as roughness and compliance, manifest themselves in the spatial patterns of this signal and can be extracted using pattern classification techniques. For legged robots, different limb-terrain interactions generate gait bounce signals with different information content, thus deliberate limb motions can effect higher information content (i.e. the robot is an active sensor of terrain class). Segmentation of the gait cycle based on the limb-terrain interaction isolates portions of the gait bounce signal with high information content. The decoding of, then sequencing of, this content from each cycle segment yields a robust classification of terrain type from known benchmarks. To extract this spatio-temporal pattern of the gait bounce signal, we developed a meta-classifier using discriminant analysis and hidden Markov model. We present the gait bounce derivation. We demonstrate the viability of terrain classification for legged vehicles using gait bounce with a rigorous study of more than 700 trials, obtaining 84% accuracy. We describe how terrain classification can be used for gait adaptation, particularly in relation to an efficiency metric. We also demonstrate that our technique is generally applicable to other locomotion mechanisms such as wheels and treads.

关键词： data mining Legged locomotion Robot sensing systems Remotely operated vehicles Terrain mapping Cameras visual servoing Pattern classification Signal generators Decoding

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Applying Differentially Variable Component analysis (dVCA) to Event‐related Potentials

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AIP conference Proceedings 2004年第1期707卷 167-181页

作者： Ankoor S. Shah Kevin H. Knuth Peter Lakatos Charles E. Schroeder *Department of Neuroscience Albert Einstein College of Medicine Bronx NY 10461 †Cognitive Neuroscience & Schizophrenia Nathan Kline Institute Orangeburg NY 10962 **Computational Sciences Division NASA Ames Research Center Moffett Field CA 94035

Event‐related potentials (ERPs) generated in response to multiple presentations of the same sensory stimulus vary from trial to trial. Accumulating evidence suggests that this variability relates to a similar trial‐to‐trial variation in the perception of the stimulus. In order to understand this variability, we previously developed differentially Variable Component analysis (dVCA) as a method for defining dynamical components that contribute to the ERP. The underlying model asserted that: (i) multiple components comprise the ERP; (ii) these components vary in amplitude and latency from trial to trial; and (iii) these components may co‐vary. A Bayesian framework was used to derive maximum a posteriori solutions to estimate these components and their latency and amplitude variability. Our original goal in developing dVCA was to produce a method for automated estimation of components in ERPs. However, we discovered that it is better to apply the algorithm in stages because of the complexity of the ERP and to use the results to define interesting subsets of the data, which are further analyzed independently. This paper describes this method and illustrates its application to actual neural signals recorded in response to a visual stimulus. Interestingly, dVCA of these data suggests two distinct response modes (or states) with differing components and variability. Furthermore, analyses of residual signals obtained by subtracting the estimated components from the actual data illustrate gamma‐frequency (circa 40 Hz) oscillations, which may underlie communication between various brain regions. These findings demonstrate the power of dVCA and underscore the necessity to apply this algorithm in a guided rather than a ballistic fashion. Furthermore, they highlight the need to examine the residual signals for those features of the signals that were not anticipated and not modeled in the derivation of the algorithm.

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Prefetching for visual data exploration 8

Prefetching for visual data exploration

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8th International conference on database Systems for Advanced Applications

作者： Doshi, PR Rundensteiner, EA Ward, MO Worcester Polytech Inst Dept Comp Sci Worcester MA 01609 USA

ISBN: (纸本)0769518958

Modern computer applications, from business decision support to scientific data analysis, utilize data visualization tools to support exploratory activities. visual exploration tools typically do not scale well when applied to huge data sets, partially because being interactive necessitates real-time responses. However we observe that interactive visual explorations exhibit several properties that can be exploited for data access optimization, including locality of exploration, contiguous queries, and significant delays between user operations. We thus apply semantic caching of active query sets on the client side to exploit some of the above characteristics. We also introduce several prefetching strategies, each exploiting characteristics of our visual exploration environment. We have incorporated caching and prefetching strategies into XmdvTool, a public-domain tool for visual exploration of multivariate data sets. Experimental studies using synthetic as well as real user traces are conducted. Our results demonstrate that these proposed optimization techniques achieve significant performance improvements in our exploratory analysis system.

关键词： Computer applications Computer science data analysis data visualization Delay Marketing and sales Navigation Performance analysis Prefetching Stock markets

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INSPECT:: A dynamic visual query system for geospatial information exploration

<i>INSPECT</i>:: A dynamic visual query system for geospatia...

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10th Annual conference on visualization and data analysis

作者： Lee, SJ Hahn, JK Powell, AM Greene, G George Washington Univ Inst Comp Graph Washington DC 20052 USA

ISBN: (纸本)0819448095

This paper presents a visual information exploration tool called INSPECT. INSPECT provides geospatial information analysts with an effective way to visually filter multidimensional data and explore the underlying information contained within it. In geospatial intelligence information analyses, it is necessary to query, visualize and understand the data combined with location information. These operations are not simple since they include complex database queries of both spatial and non-spatial data. Moreover, analysts need to repeatedly query and visualize data until they reach a desirable conclusion. Using INSPECT, analysts are able to experimentally query the database avoiding complex database schema and visualize the results in geospatial context with minimal effort. The tools available with INSPECT include see-through lens visualization, relationship visualization, time varying analysis, saved lens-filter sessions, a data reachback capability, and iterative visual exploration.

关键词： information visualization visual query lens filter visual analysis

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Pushing the limit in visual data exploration: Techniques and applications

Pushing the limit in visual data exploration: Techniques and...

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26th Annual German conference on Artificial Intelligence, KI 2003

作者： Keim, Daniel A. Panse, Christian Schneidewind, Jörn Sips, Mike Hao, Ming C. Dayal, Umeshwar University of Konstanz Germany Hewlett Packard Research Laboratories Palo AltoCA United States

ISBN: (纸本)3540200592

With the rapid growth in size and number of available databases, it is necessary to explore and develop new methods for analysing the huge amounts of data. Mining information and interesting knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Analyzing the huge amount (usually tera-bytes) of data obtained from large databases such as credit card payments, telephone calls, environmental records, census demographics, however, a very difficult task. visual exploration and visual data Mining techniques apply human visual perception to the exploration of large data sets and have proven to be of high value in exploratory data analysis. Presenting data in an interactive, graphical form often opens new insights, encouraging the formation and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper we give a short overview of visual exploration techniques and present new results obtained from applying PixelBarCharts in sales analysis and internet usage management. © Springer-Verlag Berlin Heidelberg 2003.

关键词： database systems

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