Preview: IEEE Computer Graphics and Applications
IEEE Computer Graphics and Applications
IEEE Computer Graphics and Applications bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a unique combination of peer-reviewed feature articles and informal departments, including
Published: Mon, 3 Nov 2014 15:34:29 GMT
PrePrint: Identifying 3D Geometric Shapes with a Vibrotactile Glove
The emergence of new off-screen interaction devices is bringing the field of Virtual Reality to a broad range of applications and means that virtual objects can be manipulated without the use of the traditional peripherals. However, in order to increase the sensation of reality and facilitate interaction, other stimuli need to be included. We therefore propose the incorporation of haptic feedback to assist in the execution of manipulative tasks and improve user experience in these new environments. To this end, we designed a new haptic display based on a vibrotactile glove that includes several solutions to control vibration and allow the user to feel gentle sensations. The actuator position is specifically designed to enhance the border detection capacity required for the object recognition task. We also performed an experiment with sixteen participants to evaluate the ability of our proposal in the highly demanding task of identifying 3D objects without visual feedback. Finally, the results demonstrate the capacity of this technology in practical applications and we indicate some possible lines for future research.
PrePrint: Visualization Beyond the Desktop - the next big thing
Visualization is coming of age: with visual depictions being seamlessly integrated into documents and data visualization techniques being used to understand datasets that are ever-growing in size and complexity, the term visualization is becoming used in everyday conversations. But we are on a cusp; visualization researchers need to develop and adapt to today's new devices and tomorrows technology. Today, we are interacting with visual depictions through a mouse. Tomorrow, we will be touching, swiping, grasping, feeling, hearing, smelling and even tasting our data. The next big thing is multi-sensory visualization that goes beyond the desktop.
PrePrint: The Reality Deck - Immersive Gigapixel Display
We designed and built a next-generation visualization facility, the Reality Deck, that simultaneously offers state-of-the-art aggregate resolution and immersion. The Reality Deck is a 1.5 gigapixel immersive tiled display with a 360º horizontal field of view. Comprised of 416 high density LCD displays, it is built to visualize today's gigapixel resolution data while providing users with 20/20 visual acuity for the majority of the visualization space. In this article, we discuss the motivations, design principles and engineering challenges behind the Reality Deck. Additionally, we showcase several techniques that were developed on the facility, focused on enabling natural exploration and supporting the visual analysis of gigapixel resolution 2D and 3D datasets.
PrePrint: A Graph-based Method to Detect Rare Events: An Application to Identify Pathologic Cells
Detection of outliers and anomalous behavior is a well-known problem in the data mining and statistics fields. Although the problem of identifying single outliers has been extensively studied in the literature, little or some effort has been devoted to the detection of small groups of outliers that are similar to each other but markedly different from the entire population. Many real world scenarios have small groups of outliers, e.g. a group of students that excel in a classroom or a group of spammers in an online social network. In this paper, we propose a novel method to solve this challenging problem that lies at the frontiers of outlier detection and clustering of similar groups. The method transforms a multidimensional dataset into a graph, applies a network metric to detect clusters and renders a representation for visual assessment to find rare events. We test the proposed method to detect pathologic cells (e.g. Cancer, HIV, CVA, etc.) in the biomedical science domain. The results are very promising and confirm the available ground truth provided by the domain experts.
PrePrint: A Visual Analytics System for Railway Safety Management
The working environment of railways is challenging and complex and often involves high-risk operations which affect both the company staff and inhabitants of the towns and cities alongside the railway lines. Rail companies adopt several strategies to reduce the exposure to risk of their employees and the public, which involve having trained personnel, safety technologies and work practices. However, despite this, railways remain high-risk operations and unfortunate incidents still occur. In this paper a visual analytics system is employed to help in the management of railway safety. This system is based on a data analytics workflow to compile an incident risk index which processes information that has been collated with regard to incidents along the railway tracks. The results of this data analytics workflow (i.e. incident risk index) are then displayed in a visual form in a geographical map together with socioeconomic information about the towns and cities concerned. Feedback on this visual analytics system suggests that it can be used by safety engineers and specialists when making decisions and communicating these decisions.
PrePrint: Applying a Sunburst Visualization to Summarize User Navigation Sequences
For many web-based applications, it is important to be able to analyze the paths that users have taken through the site, for example to understand how users are discovering engaging content. These paths are difficult to summarize visually because of the complexity of the underlying data. This article describes how I applied a sunburst visualization to this problem, by simplifying the data into a hierarchical format. The resulting visualization was very successful within YouTube and is widely referenced and accessed. The code for the visualization is available as open source.
PrePrint: From Data to Insight: Work Practices of Analysts in the Enterprise
With greater availability of data, businesses are increasingly becoming data-driven enterprises, establishing standards to data acquisition, processing, infrastructure, and decision making. There are now people in enterprises whose entire job role involves performing analytic work in support of decision-makers. In order to better understand analytic work, particularly the role of the enterprise business analysts, we conducted interviews with 34 analysts working in a large corporation. We found that analytical work takes place in an ecosystem of data, tools, and people; overall quality and efficiency of the ecosystem depends on the degree coordination and collaboration is supported; and analysts play a key bridge role between business and IT, in closing the semantic gap between datasets, tools, and people. In this paper, we provide an overview of the analytic work in the enterprise describing challenges in data, tools, and practices and identify opportunities for new tools to support collaborative analytic work.
PrePrint: Business Intelligence from Social Media: A Study from the VAST Box Office Challenge
With over 16 million Tweets per hour, 600 new blogs posts per minute and 400 million active users on Facebook, businesses have begun searching for ways to turn real-time consumer based posts into actionable intelligence. The goal is to extract information from this noisy, unstructured data and use it for trend analysis and prediction. Current practices support the notion visual analytics can play a large role in enabling the effective analysis of such data. However, empirical evidence demonstrating the effectiveness of a visual analytics solution is still lacking. This paper presents a visual analytics system which extracts data from Bitly and Twitter to use for box office revenue and user rating predictions. Results from the VAST Box Office Challenge 2013 demonstrate the benefit of an interactive environment for predictive analysis compared to a purely statistical modeling approach. These visual analysis method used in our system can be generalized to other domain where social media data is involved, such as sales forecasting, advertisement analysis, etc.
PrePrint: Interactive Visual Analysis of Heterogeneous Cohort Study Data
Cohort studies are used in medicine to enable the study of medical hypotheses in large samples. Often, a large amount of heterogeneous data is acquired from many subjects. The analysis is usually hypothesis-driven, i.e., a specific subset of such data is studied to confirm or reject specific hypotheses. In this paper, we demonstrate how we enable the interactive visual exploration and analysis of such data, helping with the generation of new hypotheses and contributing to the process of validating them. We propose a data-cube based model which allows to handle partially overlapping data subsets during the interactive visualization. This model enables the seamless integration of the heterogeneous data, as well as the linking of spatial and non-spatial views on these data. We implemented this model in an application prototype, and used it to analyze data acquired in the context of a cohort study on cognitive aging. In this paper we present a case-study analysis of selected aspects of brain connectivity by using a prototype implementation of the presented model, to demonstrate its potential and flexibility.