Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00030
Christian Blecha, Felix Raith, G. Scheuermann, T. Nagel, O. Kolditz, Jobst Maßsmnnn
The use of clean and renewable energy and the abandoning of fossil energy have become goals of many national and international energy policies. But even when once accomplished, mankind has to take charge of the relics of the current energy supply system. For example, due to its harmful effects, nuclear waste has to be isolated from the biosphere safely and for sufficiently long times. The geological subsurface is considered as a promising option for the deposition of such by-or end products. In order to investigate the long-term evolution of a repository system, a multiphysics simulation was performed. It combines the structural mechanics of the host rock, the fluid dynamics of formation fluids, and the thermodynamics of all materials resulting in a highly multivariate data set. A visualization of such multiphysics data challenges the current methodology. In this article, we demonstrate how an analysis of a carefully selected subset of the variables in attribute space allows to visualize and interpret the simulation data. We apply a fiber surface extraction algorithm to explore the relationships between these variables. Studying the temporal evolution in attribute space, we found a regionally bulge that could be identified as an effect of the nuclear waste repository because it can be clearly separated from the natural geophysical state prior to waste disposal. Furthermore, we used the extracted fiber surface as a starting point to examine the distribution of other variables inside this area of the physical domain. We conclude this case study with lessons learned from the visualization as well as the geotechnical side.
{"title":"Analysis of Coupled Thermo-Hydro-Mechanical Simulations of a Generic Nuclear Waste Repository in Clay Rock Using Fiber Surfaces","authors":"Christian Blecha, Felix Raith, G. Scheuermann, T. Nagel, O. Kolditz, Jobst Maßsmnnn","doi":"10.1109/PacificVis.2019.00030","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00030","url":null,"abstract":"The use of clean and renewable energy and the abandoning of fossil energy have become goals of many national and international energy policies. But even when once accomplished, mankind has to take charge of the relics of the current energy supply system. For example, due to its harmful effects, nuclear waste has to be isolated from the biosphere safely and for sufficiently long times. The geological subsurface is considered as a promising option for the deposition of such by-or end products. In order to investigate the long-term evolution of a repository system, a multiphysics simulation was performed. It combines the structural mechanics of the host rock, the fluid dynamics of formation fluids, and the thermodynamics of all materials resulting in a highly multivariate data set. A visualization of such multiphysics data challenges the current methodology. In this article, we demonstrate how an analysis of a carefully selected subset of the variables in attribute space allows to visualize and interpret the simulation data. We apply a fiber surface extraction algorithm to explore the relationships between these variables. Studying the temporal evolution in attribute space, we found a regionally bulge that could be identified as an effect of the nuclear waste repository because it can be clearly separated from the natural geophysical state prior to waste disposal. Furthermore, we used the extracted fiber surface as a starting point to examine the distribution of other variables inside this area of the physical domain. We conclude this case study with lessons learned from the visualization as well as the geotechnical side.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124789560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00029
Yan-Chao Wang, Q. Zhang, F. Lin, S. H. Soon
The heart of every vehicle is its engine. Many factors, either internal or external, contribute to the aircraft engine's durability and lifespan. In this paper, we aim to assist the analyst with a qualitative analysis of the possible external cause of engine failures. We work closely with domain experts to study the domain knowledge, analyze challenging tasks, and abstract user requirements. We present EngineQV, a visualization system that integrates multiple geo-temporal engine-associated records. It provides intuitive exploration and understanding of the data from various aspects. The system features a dynamic query on the datasets and incorporates several customized interactive visualizations. A user may query a certain group of engines or compare multiple engine groups, identify an issue, and find its potential causes. The functionality and usability of EngineQV are evaluated by two case studies, through knowledge discovery from records of a single engine and visual comparison of multiple engines. The validity of the system is confirmed by expert feedback.
{"title":"EngineQV: Investigating External Cause of Engine Failures Based on Geo-Temporal Association","authors":"Yan-Chao Wang, Q. Zhang, F. Lin, S. H. Soon","doi":"10.1109/PacificVis.2019.00029","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00029","url":null,"abstract":"The heart of every vehicle is its engine. Many factors, either internal or external, contribute to the aircraft engine's durability and lifespan. In this paper, we aim to assist the analyst with a qualitative analysis of the possible external cause of engine failures. We work closely with domain experts to study the domain knowledge, analyze challenging tasks, and abstract user requirements. We present EngineQV, a visualization system that integrates multiple geo-temporal engine-associated records. It provides intuitive exploration and understanding of the data from various aspects. The system features a dynamic query on the datasets and incorporates several customized interactive visualizations. A user may query a certain group of engines or compare multiple engine groups, identify an issue, and find its potential causes. The functionality and usability of EngineQV are evaluated by two case studies, through knowledge discovery from records of a single engine and visual comparison of multiple engines. The validity of the system is confirmed by expert feedback.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"106 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134475157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00034
R. G. C. Maack, C. Gillmann, H. Hagen
Ramachandran Plots are an important tool for researchers in bio-chemistry to examine the stability of a molecule. In these plots, dihedral (torsion) angles of the protein's backbone are visualized ona plane, where different areas are known to be stable configurations. Unfortunately, the underlying atom positions are affected by uncer-tainty, which is usually captured and expressed using the b-value. For classic Ramachandran Plots, this uncertainty is not propagatedwhen computing the dihedral angles and neglected when visualizinga Ramachandran Plot. To solve this problem, this paper presentsan extended version of the Ramachandran Plot, which allows tocommunicate the uncertainty of atom positions along the compu-tation of dihedral angles and an intuitive visualization. We showthe effectiveness of the presented approach by examining differentRamachandran Plots for molecules and show how the inclusion ofuncertainty helps biochemistry researchers to determine the stabilityof a protein with higher accuracy.
{"title":"Uncertainty-Aware Ramachandran Plots","authors":"R. G. C. Maack, C. Gillmann, H. Hagen","doi":"10.1109/PacificVis.2019.00034","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00034","url":null,"abstract":"Ramachandran Plots are an important tool for researchers in bio-chemistry to examine the stability of a molecule. In these plots, dihedral (torsion) angles of the protein's backbone are visualized ona plane, where different areas are known to be stable configurations. Unfortunately, the underlying atom positions are affected by uncer-tainty, which is usually captured and expressed using the b-value. For classic Ramachandran Plots, this uncertainty is not propagatedwhen computing the dihedral angles and neglected when visualizinga Ramachandran Plot. To solve this problem, this paper presentsan extended version of the Ramachandran Plot, which allows tocommunicate the uncertainty of atom positions along the compu-tation of dihedral angles and an intuitive visualization. We showthe effectiveness of the presented approach by examining differentRamachandran Plots for molecules and show how the inclusion ofuncertainty helps biochemistry researchers to determine the stabilityof a protein with higher accuracy.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132412359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00031
A. Frasson, M. Ender, S. Weiss, Mathias Kanzler, Amrish Pandrey, J. Schumacher, R. Westermann
We present techniques to improve the understanding of pattern forming processes in Rayleigh-Bénard-type convective heat transport, through visually guided exploration of convection features in timeaveraged turbulent flows. To enable the exploration of roll-like heat transfer pathways and pattern-forming anomalies, we combine feature extraction with interactive visualization of particle trajectories. To robustly determine boundaries between circulation rolls, we propose ridge extraction in a z-averaged temperature field, and in the extracted ridge network we automatically classify topological point defects hinting at pattern forming instabilities. An importance measure based on the circular movement of particles is employed to automatically control the density of 3D trajectories and, thus, enable insights into the heat flow in the interior of rolls. A quantitative analysis of the heat transport within and across cell boundaries, as well as investigations of pattern instabilities in the vicinity of defects, is supported by interactive particle visualization including instant computations of particle density maps. We demonstrate the use of the proposed techniques to explore direct numerical simulations of the 3D Boussinesq equations of convection, giving novel insights into Rayleigh-Bénard-type convective heat transport.
{"title":"Visual Exploration of Circulation Rolls in Convective Heat Flows","authors":"A. Frasson, M. Ender, S. Weiss, Mathias Kanzler, Amrish Pandrey, J. Schumacher, R. Westermann","doi":"10.1109/PacificVis.2019.00031","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00031","url":null,"abstract":"We present techniques to improve the understanding of pattern forming processes in Rayleigh-Bénard-type convective heat transport, through visually guided exploration of convection features in timeaveraged turbulent flows. To enable the exploration of roll-like heat transfer pathways and pattern-forming anomalies, we combine feature extraction with interactive visualization of particle trajectories. To robustly determine boundaries between circulation rolls, we propose ridge extraction in a z-averaged temperature field, and in the extracted ridge network we automatically classify topological point defects hinting at pattern forming instabilities. An importance measure based on the circular movement of particles is employed to automatically control the density of 3D trajectories and, thus, enable insights into the heat flow in the interior of rolls. A quantitative analysis of the heat transport within and across cell boundaries, as well as investigations of pattern instabilities in the vicinity of defects, is supported by interactive particle visualization including instant computations of particle density maps. We demonstrate the use of the proposed techniques to explore direct numerical simulations of the 3D Boussinesq equations of convection, giving novel insights into Rayleigh-Bénard-type convective heat transport.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122584968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00023
Nozomi Aoyama, Yosuke Onoue, Yuki Ueno, H. Natsukawa, K. Koyamada
Group-in-a-box (GIB) is a graph-drawing method designed to facilitate the visualization of the group structure of a graph. GIB allows the user to simultaneously view group sizes and inter-and intra-group structures. Several GIB variants have been proposed in the literature; however, their advantages and disadvantages have not been studied from the perspective of human cognition. Therefore, herein, we used eye tracking analysis and user surveys to evaluate the user experience of four GIB variants: Squarified-Treemap GIB(ST-GIB), Croissant-and-Doughnut GIB (CD-GIB), Force-Directed GIB (FD-GIB), and Tree-Reordered GIB (TR-GIB). We found some trade-offs among the methods for each type of user task and that FD-GIB and TR-GIB are superior than the other variants. Although ST-GIB's results were good, links were difficult to read in this graph layout. Eye-tracking data was gathered to determine which elements in each visualization significantly affected user experience. The results of this study will promote the effective use of GIB to analyze networks such as social networks or web graphs.
{"title":"User Evaluation of Group-in-a-Box Variants","authors":"Nozomi Aoyama, Yosuke Onoue, Yuki Ueno, H. Natsukawa, K. Koyamada","doi":"10.1109/PacificVis.2019.00023","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00023","url":null,"abstract":"Group-in-a-box (GIB) is a graph-drawing method designed to facilitate the visualization of the group structure of a graph. GIB allows the user to simultaneously view group sizes and inter-and intra-group structures. Several GIB variants have been proposed in the literature; however, their advantages and disadvantages have not been studied from the perspective of human cognition. Therefore, herein, we used eye tracking analysis and user surveys to evaluate the user experience of four GIB variants: Squarified-Treemap GIB(ST-GIB), Croissant-and-Doughnut GIB (CD-GIB), Force-Directed GIB (FD-GIB), and Tree-Reordered GIB (TR-GIB). We found some trade-offs among the methods for each type of user task and that FD-GIB and TR-GIB are superior than the other variants. Although ST-GIB's results were good, links were difficult to read in this graph layout. Eye-tracking data was gathered to determine which elements in each visualization significantly affected user experience. The results of this study will promote the effective use of GIB to analyze networks such as social networks or web graphs.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133823110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00011
Cheng Li, Han-Wei Shen
Data deformation has been widely used in visualization to obtain an improved view that better helps the comprehension of the data. It has been a consistent pursuit to conduct interactive deformation by operations that are natural to users. In this paper, we propose a deformation system following the object-in-hand metaphor. We utilize a touchscreen to directly manipulate the shape of the data by using fingers. Users can drag data features and move them along with the fingers. Users can also press their fingers to hold other parts of the data fixed during the deformation, or perform cutting on the data using a finger. The deformation is executed using a physically-based mesh, which is constructed to incorporate data properties to make the deformation authentic as well as informative. By manipulating data features as if handling an object in hand, we can successfully achieve less occluded view of the data, or improved feature layout for better view comparison. We present case studies on various types of scientific datasets, including particle data, volumetric data, and streamlines.
{"title":"Object-in-Hand Feature Displacement with Physically-Based Deformation","authors":"Cheng Li, Han-Wei Shen","doi":"10.1109/PacificVis.2019.00011","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00011","url":null,"abstract":"Data deformation has been widely used in visualization to obtain an improved view that better helps the comprehension of the data. It has been a consistent pursuit to conduct interactive deformation by operations that are natural to users. In this paper, we propose a deformation system following the object-in-hand metaphor. We utilize a touchscreen to directly manipulate the shape of the data by using fingers. Users can drag data features and move them along with the fingers. Users can also press their fingers to hold other parts of the data fixed during the deformation, or perform cutting on the data using a finger. The deformation is executed using a physically-based mesh, which is constructed to incorporate data properties to make the deformation authentic as well as informative. By manipulating data features as if handling an object in hand, we can successfully achieve less occluded view of the data, or improved feature layout for better view comparison. We present case studies on various types of scientific datasets, including particle data, volumetric data, and streamlines.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116812549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00032
Adam Jurcík, K. Furmanová, J. Byška, Vojtěch Vonásek, O. Vávra, Pavol Ulbrich, H. Hauser, B. Kozlíková
In many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.
{"title":"Visual Analysis of Ligand Trajectories in Molecular Dynamics","authors":"Adam Jurcík, K. Furmanová, J. Byška, Vojtěch Vonásek, O. Vávra, Pavol Ulbrich, H. Hauser, B. Kozlíková","doi":"10.1109/PacificVis.2019.00032","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00032","url":null,"abstract":"In many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115114354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00018
J. Matute, Marcel Fischer, A. Telea, L. Linsen
Principal curves are a long-standing and well-known method for summarizing large scatterplots. They are defined as self-consistent curves (or curve sets in the more general case) that locally pass through the middle of the scatterplot data. However, computing principal curves that capture well complex scatterplot topologies and are robust to noise is hard and/or slow for large scatterplots. We present a fast and robust approach for computing principal graphs (a generalization of principal curves for more complex topologies) inspired by the similarity to medial descriptors (curves locally centered in a shape). Compared to state-of-the-art methods for computing principal graphs, we outperform these in terms of computational scalability and robustness to noise and resolution. We also demonstrate the advantages of our method over other scatterplot summarization approaches.
{"title":"Scatterplot Summarization by Constructing Fast and Robust Principal Graphs from Skeletons","authors":"J. Matute, Marcel Fischer, A. Telea, L. Linsen","doi":"10.1109/PacificVis.2019.00018","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00018","url":null,"abstract":"Principal curves are a long-standing and well-known method for summarizing large scatterplots. They are defined as self-consistent curves (or curve sets in the more general case) that locally pass through the middle of the scatterplot data. However, computing principal curves that capture well complex scatterplot topologies and are robust to noise is hard and/or slow for large scatterplots. We present a fast and robust approach for computing principal graphs (a generalization of principal curves for more complex topologies) inspired by the similarity to medial descriptors (curves locally centered in a shape). Compared to state-of-the-art methods for computing principal graphs, we outperform these in terms of computational scalability and robustness to noise and resolution. We also demonstrate the advantages of our method over other scatterplot summarization approaches.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128809043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00039
Paul Craig, Yiwen Wang, Joon Sik Kim, Gang Chen, Yu Liu, Jiabei Li, Zhiqiang Gao, Gao Du
This paper describes the Smart Survey Tool, a novel multi-device application for museum visitor tracking and tracking data visualization. The application allows museum staff to capture detailed information describing how visitors move around an exhibition and interact with individual exhibits. They can then visualize the results of tracking either on a single mobile device or with multiple mobile devices connected to a large display. The platform uses orthogonal views of the exhibition space for tracking and visualization, with a chess-piece icon to represent visitors during tracking, and curved semi-transparent lines with animated semi-circles to communicate the path and direction of visitor movement. Our visualization is novel in its use of an orthogonal projection for pedestrian tracking and animation to communicate the flow of visitors around the exhibition space, as well as allowing users to dynamically switch between views representing different groups of visitors. The design of our application was informed through an extensive requirements analysis study conducted with Nanjing Museum and evaluated by conducting expert interviews with museum managers who considered that the application allowed for more effective and efficient recording and analysis of visitor tracking data.
{"title":"Smart Survey Tool: A Multi Device Platform for Museum Visitor Tracking and Tracking Data Visualization","authors":"Paul Craig, Yiwen Wang, Joon Sik Kim, Gang Chen, Yu Liu, Jiabei Li, Zhiqiang Gao, Gao Du","doi":"10.1109/PacificVis.2019.00039","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00039","url":null,"abstract":"This paper describes the Smart Survey Tool, a novel multi-device application for museum visitor tracking and tracking data visualization. The application allows museum staff to capture detailed information describing how visitors move around an exhibition and interact with individual exhibits. They can then visualize the results of tracking either on a single mobile device or with multiple mobile devices connected to a large display. The platform uses orthogonal views of the exhibition space for tracking and visualization, with a chess-piece icon to represent visitors during tracking, and curved semi-transparent lines with animated semi-circles to communicate the path and direction of visitor movement. Our visualization is novel in its use of an orthogonal projection for pedestrian tracking and animation to communicate the flow of visitors around the exhibition space, as well as allowing users to dynamically switch between views representing different groups of visitors. The design of our application was informed through an extensive requirements analysis study conducted with Nanjing Museum and evaluated by conducting expert interviews with museum managers who considered that the application allowed for more effective and efficient recording and analysis of visitor tracking data.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133044842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-23DOI: 10.1109/PacificVis.2019.00045
Teng-Yok Lee, K. Wittenburg
Development of object detectors for video in applications such as autonomous driving requires an iterative training process with data that initially requires human labeling. Later stages of development require tuning a large set of parameters that may not have labeled data available. For each training iteration and parameter selection decision, insight is needed into object detector performance. This work presents a visualization method called Space-Time Slicing to assist a human developer in the development of object detectors for driving applications without requiring labeled data. Space-Time Slicing reveals patterns in the detection data that can suggest the presence of false positives and false negatives. It may be used to set such parameters as image pixel size in data preprocessing and confidence thresholds for object classifiers by comparing performance across different conditions.
{"title":"Space-Time Slicing: Visualizing Object Detector Performance in Driving Video Sequences","authors":"Teng-Yok Lee, K. Wittenburg","doi":"10.1109/PacificVis.2019.00045","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00045","url":null,"abstract":"Development of object detectors for video in applications such as autonomous driving requires an iterative training process with data that initially requires human labeling. Later stages of development require tuning a large set of parameters that may not have labeled data available. For each training iteration and parameter selection decision, insight is needed into object detector performance. This work presents a visualization method called Space-Time Slicing to assist a human developer in the development of object detectors for driving applications without requiring labeled data. Space-Time Slicing reveals patterns in the detection data that can suggest the presence of false positives and false negatives. It may be used to set such parameters as image pixel size in data preprocessing and confidence thresholds for object classifiers by comparing performance across different conditions.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126407016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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