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International Conference on Information Visualisation (IV)

作者： Yuejun Guo Qing Xu Xiu Li Xiaoxiao Luo Mateu Sbert School of Computer Science and Technology Tianjin University Tianjin China Graphics and Imaging Laboratory Universitat de Girona Girona Spain

This paper proposes a new approach for trajectory clustering and visualization. During clustering, speed and direction are both taken into account as the important properties of a trajectory. Additionally, the temporal change of the trajectories is explicitly considered in the procedure of clustering. Importantly, we introduce the uncertainty to represent the homogeneity of the updating trajectories based on their speed and direction attributes, to help observe and understand the happening of the trajectory data. Finally, based on the use of the HSV color space, we devise three patterns for graphically presenting the trajectory data in different perspectives. Namely, 'H+S' visualizes the clustered trajectories emphasizing the speed attribute of them. 'H+S+Update' depicts more information on the "latest" trajectory data, compared with the results by 'H+S'. 'H+V+Update' explicitly presents the uncertainty of the trajectory data. Our approach has shown its potential for the effective trajectory analysis.

关键词： Trajectory Uncertainty Visualization Data visualization Image color analysis Clustering algorithms Aircraft

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User-guided Compressed Sensing for Magnetic Resonance Angiography

User-guided Compressed Sensing for Magnetic Resonance Angiog...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Changgong Zhang Martijn van de Giessen Elmar Eisemann Anna Vilanova Section of Computer Graphics and Visualization Delft University of Technology Division of Image Processing Department of Radiology Leiden University Medical Center

ISBN: (纸本)9781424479276

Compressed sensing (CS) magnetic resonance imaging (MRI) enables the reconstruction of MRI images with fewer samples in k-space. One requirement is that the acquired image has a sparse representation in a known transform domain. MR angiograms are already sparse in the image domain. They can be further sparsified through finite-differences. Therefore, it is a natural application for CS-MRI. However, low-contrast vessels are likely to disappear at high under-sampling ratios, since the commonly used l_1 reconstruction tends to underestimate the magnitude of the transformed sparse coefficients. These vessels, however, are likely to be clinically important for medical diagnosis. To avoid the fading of low-contrast vessels, we propose a user-guided CS MRI that is able to mitigate the reduction of vessel contrast within a region of interest (ROI). Simulations show that these low-contrast vessels can be well maintained via our method which results in higher local quality compared to conventional CS.

关键词： Image reconstruction Magnetic resonance imaging Compressed sensing Minimization Angiography Transforms Fading

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F-DIVERGENCES DRIVEN VIDEO KEY FRAME EXTRACTION

F-DIVERGENCES DRIVEN VIDEO KEY FRAME EXTRACTION

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IEEE International Conference on Multimedia and Expo

作者： Xiaoxiao Luo Qing Xu Mateu Sbert Klaus Schoeffmann School of Computer Science and Technology Tianjin University Graphics and Imaging Laboratory Universitat de Girona Alpen-Adria-Universitat Klagenfurt

ISBN: (纸本)9781479947607

This paper proposes a shot-based key frame selection technique, aiming at generating a condensed set of frames representing the essential content of a video sequence. Inspired by the successful utilization of Jensen-Shannon Divergence (JSD) and Jensen-Renyi Divergence (JRD) for key frame selection [1] [2], we investigate several popularly accepted f-divergences for calculating the frame-by-frame distance to segment the video clip and then to obtain the key frames. Based on simulation and real test videos, the performances of the key frame selection method by using different versions of f-divergences are systematically analyzed. Extensive experimentation shows that, compared with the methods using JSD and JRD, the new technique is slightly better and computationally faster.

关键词： Key frame selection F-divergences Jensen-Shannon Divergence (JSD) Jensen-Renyi Divergence (JRD)

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Determination of legal majority age from 3D magnetic resonance images of the radius bone

Determination of legal majority age from 3D magnetic resonan...

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IEEE International Symposium on Biomedical Imaging

作者： Darko Stern Thomas Ebner Horst Bischof Martin Urschler Institute for Computer Graphics and Vision Graz University of Technology Austria Ludwig Boltzmann Institute for Clinical Forensic Imaging Graz Austria

The determination of an individual's legal majority age is becoming increasingly important in forensic practice. Established age estimation methods are based on 2D X-rays, but suffer from problems due to projective imaging and exposure to ionizing radiation, which, without proper medical or criminal indication, is ethically questionable and legally prohibited in many countries. We propose an automatic 3D method for the determination of legal maturity from MR images based on the ossification of the radius bone. Age estimation is performed by a linear regression model of the epiphyseal gap volume over the known ground truth age of training data. Results are comparable with the established Greulich/Pyle (GP) and Tanner/Whitehouse (TW) methods, but do not involve harmful radiation.

关键词： Bones Three-dimensional displays Image segmentation Law Estimation Training data

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Exploring engineering students' college experiences using social media monitoring tool radian6

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computers in Education Journal 2013年第1期23卷 90-104页

作者： Chen, Xin Vorvoreanu, Mihaela Madhavan, Krishna School of Engineering Education Computer Graphics Technology Purdue University United States

Students nowadays talk about their college life in various online social media platforms such as Twitter, Facebook, and many blogs and forums. Public discourse on these social media sites can provide insights into students' college experiences. This paper focuses on exploring the informal social media data created by students in their daily life, rather than investigating the formal usage of social media platforms in the classroom settings. Many social media monitoring tools are developed for monitoring business brands or public events. These tools may also be used to collect social media data for educational research and policy recommendation purposes. This study uses social media monitoring tool Radian6 to collect data from Twitter about engineering students' college experiences. The data are analyzed both in Radian6 and manually using qualitative content analysis. The results shed light into the academic context and social context of engineering students' learning experiences. This exploratory study also considers the potential of social media analytics tools for engineering education research. Social media analytics tools specifically for educational purposes need to be developed in the future.

关键词： Students

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Visualization in connectomics

Mathematics and Visualization

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Mathematics and Visualization 2014年 37卷 221-245页

作者： Pfister, Hanspeter Kaynig, Verena Botha, Charl P. Bruckner, Stefan Dercksen, Vincent J. Hege, Hans-Christian Roerdink, Jos B.T.M. School of Engineering and Applied Sciences Harvard University 33 Oxford St CambridgeMA02138 United States Vxlabs Somerset West South Africa Institute of Computer Graphics and Algorithms Vienna University of Technology Favoritenstraße 9-11/E186 Wien1040 Austria Department of Visualization and Data Analysis Zuse Institute Berlin Takustraße 7 Berlin14195 Germany Johann Bernoulli Institute for Mathematics and Computer Science University of Groningen P.O. Box 407 AK Groningen9700 Netherlands

Connectomics is a branch of neuroscience that attempts to create a connectome, i.e., a completemap of the neuronal system and all connections between neuronal structures. This representation can be used to understand how functional brain states emerge from their underlying anatomical structures and how dysfunction and neuronal diseases arise. We review the current state-of-the-art of visualization and image processing techniques in the field of connectomics and describe a number of challenges. After a brief summary of the biological background and an overview of relevant imaging modalities, we review current techniques to extract connectivity information from image data at macro-, meso- and *** also discuss data integration and neural network modeling, as well as the visualization, analysis and comparison of brain networks. © 2014, Springer-Verlag London.

关键词： Visualization

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A graphics design framework to visualize multi-dimensional economic datasets

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Engineering Design graphics Journal 2013年第3期77卷 1-14页

作者： Chandramouli, Magesh Narayanan, Badri Bertoline, Gary R. Computer Graphics Technology Purdue University Calumet United States Center for Global Trade Analysis Purdue University United States College of Technology United States Department of Computer Graphics Technology Purdue University United States Department of Computer and Information Technology Purdue University United States

This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a 'visual analytical database' for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of data and more importantly, communicate the extracted information. Using a multidimensional framework not only significantly enhances the ability to view multiple variables, but also brings together diverse data formats on one canvas. Economists cope with huge multi-dimensional data sets on a day-to-day basis. Various graphic and tabulation methods have been used for methodically representing and analyzing such colossal data. However, not much effort has been directed towards applying desktop Virtual Reality (dVR) based technologies to visualize such multidimensional economic data sets. Such procedures enable data visualization without compromising the richness of preserving multiple dimensions relevant to the analytic questions in consideration. We demonstrate the possibility of such an application to a widely used time-series bilateral multi-sector trade dataset. Usefulness of this framework and application is shown using several analytical and numerical examples.

关键词： Data visualization

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Feedback-based smartphone strategic sampling for BYOD security

Feedback-based smartphone strategic sampling for BYOD securi...

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International Conference on computer Communications and Networks (ICCCN)

作者： Feng Li Chin-Tser Huang Jie Huang Wei Peng Department of Computer Information and Graphics Technology Department of Computer and Information Science Indiana University-Purdue University Indianapolis Indianapolis IN U.S.A. Department of Computer Science and Engineering University of South Carolina Columbia SC U.S.A.

ISBN: (纸本)9781479935734

Bring Your Own Device (BYOD) is an information technology (IT) policy that allows employees to use their own wireless devices to access internal network at work. Mobile malware is a major security concern that impedes BYOD's further adoption in enterprises. Existing works identify the need for better BYOD security mechanisms that balance between the strength of such mechanisms and the costs of implementing such mechanisms. In this paper, based on the idea of self-reinforced feedback loop, we propose a periodic smartphone sampling mechanism that significantly improve BYOD security mechanism's effectiveness without incurring further costs. We quantify the likelihood that “a BYOD smartphone is infected by malware” by two metrics, vulnerability and uncertainty, and base the iterative sampling process on these two metrics; the updated values of these metrics are fed back into future rounds of the mechanism to complete the feedback loop. We validate the efficiency and effectiveness of the proposed strategic sampling via simulations driven by publicly available, real-world collected traces.

关键词： Malware Measurement Uncertainty Topology Wireless communication Feedback loop

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FiberScout: An Interactive Tool for Exploring and Analyzing Fiber Reinforced Polymers

FiberScout: An Interactive Tool for Exploring and Analyzing ...

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Pacific (formerly Asia-Pacific APVIS) Visualization Symposium

作者： Johannes Weissenböck Artem Amirkhanov Weimin Li Andreas Reh Alexander Amirkhanov Eduard Gröller Johann Kastner Christoph Heinzl University of Applied Sciences Upper Austria Ufa State Aviation Technical University Ufa Russia Vienna University of Technology Institute of Computer Graphics and Algorithms Vienna Austria

Advanced composites such as fiber reinforced polymers are promising candidate materials for future components as they allow integrating the continuously rising demands of industry regarding cost-effectiveness, function-orientation, integration and weight. The most important structures of fiber reinforced polymers are the individual fibers, as their characteristics (stiffness, strength, ductility, durability, etc.) to a large extent determine the properties of the final component. The main contribution of this paper is the introduction of a new system for interactive exploration and visual analysis of fiber properties in X-ray computed tomography data of fiber reinforced polymers. The presented tool uses parallel coordinates to define and configure initial fiber classes. Using a scatter plot matrix linked to the parallel coordinates the initial classification may be refined. This allows to analyze hidden relationships between individual fiber properties. 2D and 3D views depict the resulting fiber classifications. By using polar plots an intuitive rendering of the fiber orientation distribution is provided. In addition, two modules of higher abstraction are proposed: The Blob visualization creates a hull around fibers with similar characteristics. The fiber metadata visualization allows to calculate overlays for 2D and 3D views containing regional information of particular material characteristics. The proposed system has been evaluated by two groups of domain experts. Applying the presented concepts the user feedback shows that the domain experts are now able to efficiently perform tasks as classification of fibers, visualization of fiber lengths and orientations, and visualization of fiber regions. The insights gained can be forwarded to the design office as well as to material development and simulation, in order to speed up the development of novel composite components.

关键词： Data visualization Three-dimensional displays Visualization Image color analysis Plastics Pipelines

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Approximate Poisson disk sampling on mesh

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Science China(Information Sciences) 2013年第9期56卷 194-205页

作者： GENG Bo ZHANG HuiJuan WANG Heng WANG GuoPing Graphics and Interactive Technology Lab of Dept. of Computer Science Peking University The Key Lab of Machine perception and intelligent MOE

Poisson disk sampling has been widely used in many applications such as remeshing, procedural texturing, object distribution, illumination, etc. While 2D Poisson disk sampling is intensively studied in recent years, direct Poisson disk sampling on 2-manifold surface is rarely covered. In this paper, we present a novel framework which generates approximate Poisson disk distribution directly on mesh, a discrete representation of 2-manifold surfaces. Our framework is easy to implement and provides extra flexibility to specified sampling issues like feature-preserving sampling and adaptive sampling. We integrate the tensor voting method into feature detection and adaptive sample radius calculation. Remeshing as a special downstream application is also addressed. According to our experiment results, our framework is efficient, robust, and widely applicable.

关键词： Poisson disk sampling feature preserving sampling adaptive sampling remeshing tensor voting

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