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Kamijo Lab
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The lab studies how to capture traffic conditions with images and sensors to support autonomous driving.
AboutAbout the lab
Supporting traffic safety with images and sensors
Kamijo Lab researches technologies that process image and sensor information for autonomous driving and Intelligent Transport Systems (ITS).
The lab works on high-definition 3D maps (HD maps) for autonomous driving, LiDAR-based self-localization, and risk estimation in traffic scenes.
It also conducts research on analyzing human behavior from smartphone sensors and in-store camera footage.
The lab is located in the Institute of Industrial Science at the Komaba Research Campus, and many international students and researchers from abroad are part of it.
Key terms
- ITS
- Intelligent Transport Systems. Systems that use information and communication technologies to improve the safety and efficiency of road traffic.
- LiDAR
- A sensor that emits laser light and measures the distance to an object from the time it takes for the light to bounce back.
- GAN
- Generative adversarial network. A method that trains two neural networks against each other to generate realistic images and other data.
ResearchResearch themes
The lab researches technologies that capture the state of roads and people using sensors such as in-vehicle cameras, LiDAR, and smartphones, for autonomous driving and Intelligent Transport Systems. It works on sensing in bad weather, traffic scene recognition, self-localization, and 3D map generation.
*Illustrative imageSensing in Adverse Conditions
The lab generates data that reproduces how sensors perceive scenes in poor conditions such as rain, fog, and darkness. Using GANs, it converts daytime images into nighttime images and LiDAR data into data as it would appear in rain or fog.
*Illustrative imageTraffic Scene Recognition and Behavior Planning
To protect the safety of vulnerable road users such as pedestrians and cyclists, the lab studies everything from detection to action recognition. It also works on estimating the level of risk in traffic scenes and on behavior planning that lets a vehicle act like a human driver at intersections.
*Illustrative imageSurrounding Environment Recognition
This research focuses on recognizing the surroundings at places such as intersections. By combining object positions obtained from high-definition 3D maps (HD maps) with images, the lab improves the accuracy of detecting objects, especially in adverse conditions.
*Illustrative imageSelf-Localization
This research aims to let autonomous vehicles and smartphone apps know their own position accurately. Especially in urban areas, the lab aims to develop methods for high-accuracy position estimation using GNSS (satellite positioning), inertial sensors, and maps together with LiDAR.
MembersFaculty
The members of Kamijo Lab consist of faculty, doctoral and master's students, and researchers from abroad.
- Associate ProfessorShunsuke Kamijo
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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: “Red Light Intersection ( )” Dave Lauretti from Burlington, Canada / CC BY 2.0 (cropped)
- Sensing in Adverse Conditions: “A foggy night view toward an approaching car along Burlington County Route 630 (Woodlane Road) in Westampton Township, Burlington County, New Jersey” Famartin / CC BY-SA 4.0 (cropped)
- Traffic Scene Recognition and Behavior Planning: “Pedestrian and Bicycle Crossing - Pod šiancom, Košice, SK” Wkmdjay / CC0 (cropped)
- Surrounding Environment Recognition: “Moscow, Yandex self-driving Hyundai Sonata, Aug 2025 roof unit 03” Retired electrician / CC0 (cropped)
- Self-Localization: “42nd st canyon” Ad Meskens / CC BY-SA 3.0 (cropped)
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