Volume 34 (2015)

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Cell Lineage Visualisation
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Pretorius, A. Johannes; Khan, Imtiaz A.; Errington, Rachel J.; H. Carr, K.-L. Ma, and G. Santucci
Cell lineages describe the developmental history of cell populations and are produced by combining time-lapse imaging and image processing. Biomedical researchers study cell lineages to understand fundamental processes such as cell differentiation and the pharmacodynamic action of anticancer agents. Yet, the interpretation of cell lineages is hindered by their complexity and insufficient capacity for visual analysis. We present a novel approach for interactive visualisation of cell lineages. Based on an understanding of cellular biology and live-cell imaging methodology, we identify three requirements: multimodality (cell lineages combine spatial, temporal, and other properties), symmetry (related to lineage branching structure), and synchrony (related to temporal alignment of cellular events). We address these by combining visual summaries of the spatiotemporal behaviour of an arbitrary number of lineages, including variation from average behaviour, with node-link representations that emphasise the presence or absence of symmetry and synchrony. We illustrate the merit of our approach by presenting a real-world case study where the cytotoxic action of the anticancer drug topotecan was determined.
Data-driven Handwriting Synthesis in a Conjoined Manner
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Chen, Hsin-I; Lin, Tse-Ju; Jian, Xiao-Feng; Shen, I-Chao; Chen, Bing-Yu; Stam, Jos and Mitra, Niloy J. and Xu, Kun
A person's handwriting appears differently within a typical range of variations, and the shapes of handwriting characters also show complex interaction with their nearby neighbors. This makes automatic synthesis of handwriting characters and paragraphs very challenging. In this paper, we propose a method for synthesizing handwriting texts according to a writer's handwriting style. The synthesis algorithm is composed by two phases. First, we create the multidimensional morphable models for different characters based on one writer's data. Then, we compute the cursive probability to decide whether each pair of neighboring characters are conjoined together or not. By jointly modeling the handwriting style and conjoined property through a novel trajectory optimization, final handwriting words can be synthesized from a set of collected samples. Furthermore, the paragraphs' layouts are also automatically generated and adjusted according to the writer's style obtained from the same dataset. We demonstrate that our method can successfully synthesize an entire paragraph that mimic a writer's handwriting using his/her collected handwriting samples.
EasyXplorer: A Flexible Visual Exploration Approach for Multivariate Spatial Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Wu, Feiran; Chen, Guoning; Huang, Jin; Tao, Yubo; Chen, Wei; Stam, Jos and Mitra, Niloy J. and Xu, Kun
Exploring multivariate spatial data attracts much attention in the visualization community. The main challenge lies in that automatic analysis techniques is insufficient in discovering complicated patterns with the perspective of human beings, while visualization techniques are incapable of accurately identifying the features of interest. This paper addresses this contradiction by enhancing automatic analysis techniques with human intelligence in an iterative visual exploration process. The integrated system, called EasyXplorer, provides a suite of intuitive clustering, dimension reduction, visual encoding and filtering widgets within 2D and 3D views, allowing an inexperienced user to visually explore and reason undiscovered features with several simple interactions. Case studies show the quality and scalability of our approach in quite challenging examples.
Evaluating 2D Flow Visualization Using Eye Tracking
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Ho, Hsin-Yang; Yeh, I-Cheng; Lai, Yu-Chi; Lin, Wen-Chieh; Cherng, Fu-Yin; H. Carr, K.-L. Ma, and G. Santucci
Flow visualization is recognized as an essential tool for many scientific research fields and different visualization approaches are proposed. Several studies are also conducted to evaluate their effectiveness but these studies rarely examine the performance from the perspective of visual perception. In this paper, we aim at exploring how users' visual perception is influenced by different 2D flow visualization methods. An eye tracker is used to analyze users' visual behaviors when they perform the free viewing, advection prediction, flow feature detection, and flow feature identification tasks on the flow field images generated by different visualizations methods. We evaluate the illustration capability of five representative visualization algorithms. Our results show that the eye-tracking-based evaluation provides more insights to quantitatively analyze the effectiveness of these visualization methods.
Multiple Facial Image Editing Using Edge-Aware PDE Learning
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Liang, Lingyu; Jin, Lianwen; Zhang, Xin; Xu, Yong; Stam, Jos and Mitra, Niloy J. and Xu, Kun
This paper introduces a novel facial editing tool, called edge-aware mask, to achieve multiple photo-realistic rendering effects in a unified framework. The edge-aware masks facilitate three basic operations for adaptive facial editing, including region selection, edit setting and region blending. Inspired by the state-of-the-art edit propagation and partial differential equation (PDE) learning method, we propose an adaptive PDE model with facial priors for masks generation through edge-aware diffusion. The edge-aware masks can automatically fit the complex region boundary with great accuracy and produce smooth transition between different regions, which significantly improves the visual consistence of face editing and reduce the human intervention. Then, a unified and flexible facial editing framework is constructed, which consists of layer decomposition, edge-aware masks generation, and layer/mask composition. The combinations of multiple facial layers and edge-aware masks can achieve various facial effects simultaneously, including face enhancement, relighting, makeup and face blending etc. Qualitative and quantitative evaluations were performed using different datasets for different facial editing tasks. Experiments demonstrate the effectiveness and flexibility of our methods, and the comparisons with the previous methods indicate that improved results are obtained using the combination of multiple edge-aware masks.
Radiometric Transfer: Example-based Radiometric Linearization of Photographs
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Li, Han; Peers, Pieter; Jaakko Lehtinen and Derek Nowrouzezahrai
We present an example-based approach for radiometrically linearizing photographs that takes as input a radiometrically linear exemplar image and a target regular uncalibrated image of the same scene, possibly from a different viewpoint and/or under different lighting. The output of our method is a radiometrically linearized version of the target image. Modeling the change in appearance of a small image patch seen from a different viewpoint and/or under different lighting as a linear 1D subspace, allows us to recast radiometric transfer in a form similar to classic radiometric calibration from exposure stacks. The resulting radiometric transfer method is lightweight and easy to implement. We demonstrate the accuracy and validity of our method on a variety of scenes.
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Diehl, Alexandra; Pelorosso, Leandro; Delrieux, Claudio; Saulo, Celeste; Ruiz, Juan; Gröller, M. Eduard; Bruckner, Stefan; H. Carr, K.-L. Ma, and G. Santucci
Weather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For this reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical Weather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization of geo-spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a visualization system for the analysis of spatio-temporal patterns in short-term weather forecasts. For this purpose, we provide an interactive visualization interface that guides users from simple visual overviews to more advanced visualization techniques. Our solution presents multiple views that include a timeline with geo-referenced maps, an integrated webmap view, a forecast operation tool, a curve-pattern selector, spatial filters, and a linked meteogram. Two key contributions of this work are the timeline with geo-referenced maps and the curve-pattern selector. The latter provides novel functionality that allows users to specify and search for meaningful patterns in the data. The visual interface of our solution allows users to detect both possible weather trends and errors in the weather forecast model.We illustrate the usage of our solution with a series of case studies that were designed and validated in collaboration with domain experts.
Visual Analytics for Correlation-Based Comparison of Time Series Ensembles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Köthur, Patrick; Witt, Carl; Sips, Mike; Marwan, Norbert; Schinkel, Stefan; Dransch, Doris; H. Carr, K.-L. Ma, and G. Santucci
An established approach to studying interrelations between two non-stationary time series is to compute the 'windowed' cross-correlation (WCC). The time series are divided into intervals and the cross-correlation between corresponding intervals is calculated. The outcome is a matrix that describes the correlation between two time series for different intervals and varying time lags. This important technique can only be used to compare two single time series. However, many applications require the comparison of ensembles of time series. Therefore, we propose a visual analytics approach that extends the WCC to support a correlation-based comparison of two ensembles of time series. We compute the pairwise WCC between all time series from the two ensembles, which results in hundreds of thousands of WCC matrices. Statistical measures are used to derive a concise description of the time-varying correlations between the ensembles as well as the uncertainty of the correlation values. We further introduce a visually scalable overview visualization of the computed correlation and uncertainty information. These components are combined with multiple linked views into a visual analytics system to support configuration of the WCC as well as detailed analysis of correlation patterns between two ensembles. Two use cases from very different domains, cognitive science and paleoclimatology, demonstrate the utility of our approach.
Visual Analytics for Exploring Local Impact of Air Traffic
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Buchmüller, Juri; Janetzko, Halldor; Andrienko, Gennady; Andrienko, Natalia; Fuchs, Georg; Keim, Daniel A.; H. Carr, K.-L. Ma, and G. Santucci
The environmental and noise impact of airports often causes extensive political discussion which in some cases even lead to transnational tensions. Analyzing local approach and departure patterns around an airport is difficult since it depends on a variety of complex variables like weather, local and general regulations and many more. Yet, understanding these movements and the expected amount of flights during arrival and departure is of great interest to both casual and expert users, as planes have a higher impact on the areas beneath during these phases. We present a Visual Analytics framework that enables users to develop an understanding of local flight behavior through visual exploration of historical data and interactive manipulation of prediction models with direct feedback, as well as a classification quality visualization using a random noise metaphor. We showcase our approach using real world data from the Zurich International Airport region, where aircraft noise has led to an ongoing conflict between Germany and Switzerland. The use cases, findings and expert feedback demonstrate how our approach helps in understanding the situation and to substantiate the otherwise often subjective discourse on the topic.
Visual Analytics for the Exploration of Tumor Tissue Characterization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Raidou, Renata Georgia; Heide, Uulke A. van der; Dinh, Cuong Viet; Ghobadi, Ghazaleh; Kallehauge, Jesper Follsted; Breeuwer, Marcel; Vilanova, Anna; H. Carr, K.-L. Ma, and G. Santucci
Tumors are heterogeneous tissues consisting of multiple regions with distinct characteristics. Characterization of these intra-tumor regions can improve patient diagnosis and enable a better targeted treatment. Ideally, tissue characterization could be performed non-invasively, using medical imaging data, to derive per voxel a number of features, indicative of tissue properties. However, the high dimensionality and complexity of this imaging-derived feature space is prohibiting for easy exploration and analysis - especially when clinical researchers require to associate observations from the feature space to other reference data, e.g., features derived from histopathological data. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visually comparing them and mentally reconstructing their relationships. This is a time consuming and tedious process, from which it is difficult to obtain the required insight. We propose a visual tool for: (1) easy exploration and visual analysis of the feature space of imaging-derived tissue characteristics and (2) knowledge discovery and hypothesis generation and confirmation, with respect to reference data used in clinical research. We employ, as central view, a 2D embedding of the imaging-derived features. Multiple linked interactive views provide functionality for the exploration and analysis of the local structure of the feature space, enabling linking to patient anatomy and clinical reference data. We performed an initial evaluation with ten clinical researchers. All participants agreed that, unlike current practice, the proposed visual tool enables them to identify, explore and analyze heterogeneous intra-tumor regions and particularly, to generate and confirm hypotheses, with respect to clinical reference data.
Visualization of Coherent Structures of Light Transport
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Zirr, Tobias; Ament, Marco; Dachsbacher, Carsten; H. Carr, K.-L. Ma, and G. Santucci
Inspired by vector field topology, an established tool for the extraction and identification of important features of flows and vector fields, we develop means for the analysis of the structure of light transport. For that, we derive an analogy to vector field topology that defines coherent structures in light transport. We also introduce Finite-Time Path Deflection (FTPD), a scalar quantity that represents the deflection characteristic of all light transport paths passing through a given point in space. For virtual scenes, the FTPD can be computed directly using path-space Monte Carlo integration. We visualize the FTPD field for several example scenes and discuss the revealed structures. Lastly, we show that the coherent regions visualized by the FTPD are closely related to the coherent regions in our new topologically-motivated analysis of light transport. FTPD visualizations are thus also visualizations of the structure of light transport.

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Browsing Volume 34 (2015) by Subject "Applications"

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