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Katto Lab
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The lab conducts broad research on network and video technologies.
AboutAbout the lab
Researching “multimedia communications.”
Katto Lab studies communication networks and multimedia technologies.
Research is carried out in two groups: the Network Group and the Multimedia Group.
Students' own preferences are respected when choosing research topics, so each student can pursue research that interests them.
The lab works on a wide range of topics, including localization using point cloud data, video compression coding, and image recognition.
Key terms
- Point cloud data
- Three-dimensional data represented as a collection of points, each carrying position and color information
- Reinforcement learning
- A machine learning method in which a computer learns, through trial and error, which actions lead to good results
- Image recognition
- A technology that enables a computer to identify what is shown in an image
NewsLab news
A research group led by Prof. Katto developed a technology that uses AI to predict radio conditions and stabilize 5G multicast broadcasting
A master's student received the Best Poster Award at the Picture Coding Symposium of Japan
A master's student received the IE Award at the IEICE Technical Committee on Image Engineering
Two students received the Best Poster Award at the Picture Coding Symposium of Japan
A master's student received the Best Regional Paper Award at ICCE 2025
ResearchResearch themes
The lab conducts broad research on communication networks and technologies related to video and images. It works on research that combines networks and video processing, such as indoor localization, control of video streaming, and heart rate estimation.
*Illustrative imageIndoor Localization with LiDAR
The lab studies a technology that estimates one's position indoors by matching data from LiDAR sensors, which measure distance with lasers, against building maps.
*Illustrative imageLive Streaming of MR Video
Using MR devices that combine AR and VR, the lab evaluates image quality and viewing comfort when 360-degree video is live-streamed.
*Illustrative imageAI-Based Control of Video Streaming
The lab studies using reinforcement learning to automatically adjust how video is streamed, based on communication quality data collected on smartphones.
*Illustrative imageHeart Rate Estimation from Video
The lab examines the accuracy of a technology that reads blood flow from slight changes in facial color in video and estimates heart rate.
MembersFaculty
The members of Katto Lab consist of faculty, researchers, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorJiro Katto
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Studio A broadcast area ( )” Atomic Taco from Seattle, WA, USA / CC BY-SA 2.0 (cropped)
- Indoor Localization with LiDAR: “Austin Texas LiDAR Point Cloud (Highway 183)” Rebecca equator / CC BY-SA 4.0 (cropped)
- Live Streaming of MR Video: “HoloLens 2” Microsoft Sweden / CC BY 2.0 (cropped)
- AI-Based Control of Video Streaming: “Orb River weir - Roquebrun” Christian Ferrer / CC BY 4.0 (cropped)
- Heart Rate Estimation from Video: “Wrist-oximeter” UusiAjaja / CC0 (cropped)
- Related lab (文研究室): “Navigation Technology Satellite – II” U.S. Navy / Public domain (cropped)
- Related lab (前原研究室): “Advanced Technology Demonstrator radar antenna array 01” NOAA / Public domain (cropped)
- Related lab (中里研究室): “Network cables in server room” ProjectManhattan / CC BY-SA 3.0 (cropped)
- Related lab (森田研究室): “Optical fiber in protective coating that transports a Laser beam - Laser Physics Lab - NTNU-NT” NTNU, Faculty of Natural Sciences and Technology / CC BY 2.0 (cropped)
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