Scientific visualization is a key technology for efficiently obtaining new scientific knowledge and insights from a large amount of data using visual information. And it has developed mainly in the natural sciences, especially in the field of computational science, and has now widely spread to various academic fields, including not only science and engineering but also life science and social science. Recently, big data analysis and AI have increased the demand for the integration of data science and computational science to solve progressively complex scientific and social problems, and the data processed on high-performance computing environments is becoming increasingly diverse. Visualization and analysis techniques are becoming more important to obtain scientific knowledge that can be interpreted by humans from such a wide variety of large-scale data. In this paper, we review the past research on scientific visualization for numerical simulation, and discuss recent trends, challenges, and prospects for the future.

Toward a sustainable society, there is a need for enhanced telecommunication tools. In communication, social cues such as appearance, eye contact, and gestures play an important role. Compared to conventional communication tools, interaction through avatars in a 3D virtual space is promising as a future telecommunication tool because the social cues exchanged through the tool are richer and the environment can be manipulated and reconfigured in real time. What factors affect communication through avatars in virtual spaces, and how do these factors affect communication? To answer these questions, Social VR research unit of Institute for Future City Studies of Tokyo City University was established in 2020. This paper introduces four of the research projects that have been conducted so far, focusing mainly on social cues related to appearance.

There has to be much training data to apply machine learning methods for various computer vision tasks. In some of the tasks it is difficult to make ground truth labels for training images. Some researchers have tried to make training images with ground truth labels by using computer graphics. And in reinforcement learning where the agent can learn by interacting with the environment, autonomous robot with various sensors has to work in real environment. But it is difficult to make the environment. On the other hand, in the virtual environment using computer graphics, it is easy to control the environment and to get various information in the environment. Therefore the virtual environment using computer graphics is easy to use for reinforcement learning. This paper describes usage of computer graphics for making training dataset and making reinforcement learning environment.

VR/AR contents have a great impact on user's inner state through the experiences rather than seeing images. This paper discusses the effects of VR/AR contents experiences on the users' emotion, consciousness, and behavior through several experiments. The experiment on the effects of 3D and high-resolution elements in VR contents on user's emotion showed that they affect emotions such as surprise, active pleasure, and affinity. The experiment on employee's VR experiences showed that understanding product usage through VR contents experiences improve their work engagement. In addition, the experiment on AR experiences and purchasing behavior showed that atmosphere added by AR contents affects customer's emotion and influences their purchasing behavior. From these results, it is expected that the effective use of VR/AR contents will improve user's emotion, consciousness and behavior.

In the field of visualization using computer graphics, various environments have changed not only due to the effects of hardware and software evolution, but also because of the Corona Disaster. Among these, the most recent and dramatic changes include the evolution of displays, real-time graphics, the handling of large amounts of data, and the evolution of image production procedures. The enhancement of CG equipment, the decrease in the price of tools, and the penetration of cloud computing have also had a positive impact on the production environment.

This document summarizes recent developments in the computer graphics industry in 2022.