Topics that shape the future
- Closer look at research results -

My specialty is the field of computer graphics, and I am particularly researching physical simulation techniques for producing realistic images. In order to calculate the appearance of objects, research is being conducted on optical simulation techniques that reproduce light and shadow, as well as dynamic simulation techniques that calculate the movement of fluids, cloth, and collision phenomena. In optical simulation, I am researching simulations of light transport, such as when light emitted from light sources such as the sun or fluorescent lights is reflected by objects or scattered by media such as smoke, and I am also researching the estimation of the materials of objects and media. In the field of dynamic simulation, I am researching simulation techniques for fluids with complex fluidity, such as cream or sauce, and estimating the fluidity of such complex fluids in the real world.
In addition to these studies, we are also conducting research into NPR (Non-Photorealistic Rendering). For example, this is a technology to reproduce the characteristic brushstrokes of Van Gogh's oil paintings. Based on a three-dimensional scene model and several images, we are working on developing technology to generate animations that maintain the brushstrokes while taking into account the lighting, shape, and appearance of the scene. In this way, our research can be broadly divided into two genres: research into the appearance and movement of objects through simulations of light and dynamics, and research into NPR, which automatically generates images while retaining the artist's characteristics.

Yes. That's roughly how it works. For example, if there is a brush stroke in an illustration, it naturally has the direction in which the brush flowed. Then, of course, there is the color, and there is also information such as length and thickness, but we are considering how to mathematically recognize this and correctly calculate and express it when the way the light hits it or the orientation of an object changes.

I want to expand the expressiveness of computers, but I don't really want to use deep learning. One reason is that copyright issues inevitably arise when a huge amount of data is required. Furthermore, even if machine learning is used, there is the issue of not being able to clearly explain why a certain result was output. In aiming for non-realistic expressions, I am conscious of wanting to be able to use an open mathematical model to determine which elements to focus on in order to reproduce the characteristics of an artist, how to collect information, and what calculations are required to finally create the expression.

Being selected for the JST Emergent Research Support Program has been a great help. Of course, this is in terms of funding, but more than that, this program has given us many opportunities to interact with researchers from different fields, allowing us to look at our research from a variety of perspectives. Although we do not directly conduct joint research, through our conversations we often find that everyone has similar concerns, get hints that can be used in future research, and are greatly inspired.

One of the major goals of my research is to find interest not just in video production, but in a broader scientific area, and to achieve this, I want to express complex physical phenomena with simple mathematical models. In the case of the simulation of source movement that I introduced earlier, by being able to simulate how such complex mixtures move, it is expected that in the future it will be applied to fields such as disaster prediction and earth science, for example, landslides and glacier collapses.
My goal going forward is to keep a constant eye on the latest trends in cutting-edge research, update my lectures to incorporate newly developed fundamental theories and cutting-edge applied research topics, and build new mathematical models in my research, so that phenomena that were previously difficult to handle can be handled more easily.

As for the Department of Information Technology in the School of Science and Engineering, I think the relaxed atmosphere is one of its charms. Of course, there are many classes and assignments, but I think you can study at your own pace without being pressured. Whether it's a lecture or research, it's very important to be able to say "I don't understand, can you explain this?" when you don't understand something. In this department, you can face learning with a long-term perspective, so I think it's easy to develop a learning style where you stop for a moment, reflect on what you've learned so far, and then move on to the next step. I want students to take their time and learn slowly, and gain confidence that they are standing on the history of academic studies.