Visual analytics employs interactive visualizations to integrate users＇ knowledge and inference capability into numerical/algorithmic data analysis processes. It is an active research field that has applications in m...Visual analytics employs interactive visualizations to integrate users＇ knowledge and inference capability into numerical/algorithmic data analysis processes. It is an active research field that has applications in many sectors, such as security, finance, and business. The growing popularity of visual analytics in recent years creates the need for a broad survey that reviews and assesses the recent developments in the field. This report reviews and classifies recent work into a set of application categories including space and time, multivariate, text, graph and network, and other applications. More importantly, this report presents analytics space, inspired by design space, which relates each application category to the key steps in visual analytics, including visual mapping, model-based analysis, and user interactions. We explore and discuss the analytics space to acld the current understanding and better understand research trends in the field.展开更多
Direct volume rendering （DVR） is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different stru...Direct volume rendering （DVR） is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images （DVRIs）. However, end-users often feel that some risks are always associated with DVR because they do not know whether any important information is missing from the transparent regions of DVRIs. In this paper, we investigate how to semi-automatically generate a set of DVRIs and also an animation which can reveal information missed in the original DVRIs and meanwhile satisfy some image quality criteria such as coherence. A complete framework is developed to tackle various problems related to the generation and quality evaluation of visibility-aware DVRIs and animations. Our technique can reduce the risk of using direct volume rendering and thus boost the confidence of users in volume rendering systems.展开更多
基金partly supported by the National Natural Science Foundation of China under Grant No. 61070114the Program for New Century Excellent Talents in University of China under Grant No. NCET-12-1087the Zhejiang Provincial Qianjiang Talents of China under Grant No. 2013R10054
文摘Visual analytics employs interactive visualizations to integrate users＇ knowledge and inference capability into numerical/algorithmic data analysis processes. It is an active research field that has applications in many sectors, such as security, finance, and business. The growing popularity of visual analytics in recent years creates the need for a broad survey that reviews and assesses the recent developments in the field. This report reviews and classifies recent work into a set of application categories including space and time, multivariate, text, graph and network, and other applications. More importantly, this report presents analytics space, inspired by design space, which relates each application category to the key steps in visual analytics, including visual mapping, model-based analysis, and user interactions. We explore and discuss the analytics space to acld the current understanding and better understand research trends in the field.
基金supported in part by Hong Kong RGC CERG under Grant No. 618705
文摘Direct volume rendering （DVR） is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images （DVRIs）. However, end-users often feel that some risks are always associated with DVR because they do not know whether any important information is missing from the transparent regions of DVRIs. In this paper, we investigate how to semi-automatically generate a set of DVRIs and also an animation which can reveal information missed in the original DVRIs and meanwhile satisfy some image quality criteria such as coherence. A complete framework is developed to tackle various problems related to the generation and quality evaluation of visibility-aware DVRIs and animations. Our technique can reduce the risk of using direct volume rendering and thus boost the confidence of users in volume rendering systems.
