A survey of immersive visualization:Focus on perception and interaction

Immersive visualization utilizes virtual reality,mixed reality devices,and other interactive devices to create a novel visual environment that integrates multimodal perception and interaction.This technology has been maturing in recent years and has found broad applications in various fields.Based on the latest research advancements in visualization,this paper summarizes the state-of-theart work in immersive visualization from the perspectives of multimodal perception and interaction in immersive environments,additionally discusses the current hardware foundations of immersive setups.By examining the design patterns and research approaches of previous immersive methods,the paper reveals the design factors for multimodal perception and interaction in current immersive environments.Furthermore,the challenges and development trends of immersive multimodal perception and interaction techniques are discussed,and potential areas of growth in immersive visualization design directions are explored.

PubExplorer:An interactive analytical system for visualizing publication data

With the intersection and convergence of multiple disciplines and technologies,more and more researchers are actively exploring interdisciplinary cooperation outside their main research fields.Facing a new research field,researchers often hope to quickly learn what is being studied in this field,which research points are receiving high attention,which researchers are studying these research points,and then consider the possibility of collaborating with core researchers on these research points.In addition,students who are preparing for academic further education usually conduct research on mentors and mentors’research platforms,including academic connections,employment opportunities,etc.In order to satisfy these requirements,we(1)design a research point state map based on a science map to help researchers and students understand the development state of a new research field;(2)design a bar-link author-affiliation information graph to help researchers and students clarify academic networks of scholars and find suitable collaborators or mentors;(3)designs citation pattern histogram to quickly discover research achievements with high research value,such as the Sleeping Beauty papers,recently hot papers,classic papers and so on.Finally,an interactive analytical system named PubExplorer was implemented with IEEE VIS publication data,and its effectiveness is verified through case studies.

Time analysis of regional structure of large-scale particle using an interactive visual system

N-body numerical simulation is an important tool in astronomy.Scientists used this method to simulate the formation of structure of the universe,which is key to understanding how the universe formed.As research on this subject further develops,astronomers require a more precise method that enables expansion of the simulation and an increase in the number of simulation particles.However,retaining all temporal information is infeasible due to a lack of computer storage.In the circumstances,astronomers reserve temporal data at intervals,merging rough and baffling animations of universal evolution.In this study,we propose a deep-learning-assisted interpolation application to analyze the structure formation of the universe.First,we evaluate the feasibility of applying interpolation to generate an animation of the universal evolution through an experiment.Then,we demonstrate the superiority of deep convolutional neural network(DCNN)method by comparing its quality and performance with the actual results together with the results generated by other popular interpolation algorithms.In addition,we present PRSVis,an interactive visual analytics system that supports global volume rendering,local area magnification,and temporal animation generation.PRSVis allows users to visualize a global volume rendering,interactively select one cubic region from the rendering and intelligently produce a time-series animation of the high-resolution region using the deep-learning-assisted method.In summary,we propose an interactive visual system,integrated with the DCNN interpolation method that is validated through experiments,to help scientists easily understand the evolution of the particle region structure.

Visual analytics of combustion on time-varying turbulent-flow

Visualization is crucial for analyzing the turbulent combustion simulation.Time-varying data allows us to investigate the evolution process of the turbulent flow field.To study the combustion effects,we calculated the enstrophy of the flow field since high enstrophy region can display valuable features,and extract components based on these features.We isolated large components to track their behaviors and characterized them using volume and spatial locations,which helps scientists to explore the dynamics and temporal changes of intense events individually.We analyzed the components’structures and visualized them in contouring and statistical charts.