Image Informatics Laboratory

Department of Social Informatics Analytics Infrastructure Research
Academic Center for Computing and Media Studies

Affiliated: Social Informatics Analytics Infrastructure Division
Social Informatics Course, Graduate School of Informatics

for Prospective International Students

We accept students into the Master’s and Doctoral programs of the Social Informatics Course, Graduate School of Informatics.

If you are considering applying from overseas, please take a look at our guidelines first, which cover admissions, funding, and how to get in touch.

Lab Principle: All about images, toward the essence

“Image” refers not only to RGB photographs, but to any pattern that describes the features or state of an object or phenomenon. There are diverse forms of images that represent various aspects of the real world, such as depth images, spectral images, CT images, and MR images. In mathematics, “image” also means the set obtained by mapping a structure from one space to another through a function.

In Image Informatics, we comprehensively study the structures, transformations, and representations of such “images,” which appear in various descriptive spaces through sensors and computational processes, to approach the fundamental essence of the target.

  • Computational Imaging: An image is not the object itself, but a modality-dependent representation of certain aspects, determined by the method and conditions of observation. Observation can be regarded as “encoding,” while extracting fundamental patterns and structures can be seen as “decoding.” This process involves technologies such as optical design, electronics, machine learning, and optimization.
  • Understanding Motion and Deformation: Temporal changes in images are key to understanding and predicting phenomena. We use geometric and statistical approaches to model diverse types of change, such as motion constrained by skeletal structure or the dynamic deformation of clouds and biological tissues. Our goal is to achieve unified analysis of dynamic images in the real world.
  • Visualization and Expression: Effective presentation requires careful design of perspective. By selecting the most relevant information and expressing it as the optimal “image,” we support discovery and better decision-making. We also explore new methods of delivering images, not only through 2D displays but also through 3D displays, 3D printers, and other modalities.

Contact

Room 407 South Bldg.
Academic Center for Computing and Media Studies
Kyoto University
Yoshida-Nihonmatsu-cho, Sakyo-ku
Kyoto 606-8501 Japan