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Computer Vision Lab
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The lab studies computer vision, reading human movement and the appearance of objects from images.
AboutAbout the lab
Giving computers an intelligent ability to see.
The parts of the brain involved in vision are said to occupy about 40% of the cerebral cortex. Realizing computer vision as a truly intelligent means of perception is fundamental to artificial intelligence, and also leads to a better understanding of human vision.
The Computer Vision Lab (Nishino Lab) began in April 2018, when Professor Ko Nishino returned from the United States.
The results can be applied to AR/VR, graphics, human-computer interaction, and robotics, and the lab currently focuses on autonomous driving and driver assistance, as well as elderly care and daily-life support.
Key terms
- Computer vision
- Technology that lets computers understand the surrounding world from camera images and video
- Imaging
- Capturing light with a camera or similar device and turning it into an image
- LiDAR
- A sensor that shines laser light and measures distance and shape from the time it takes for the light to return
ResearchResearch themes
The lab works on four themes (seeing people, seeing objects, seeing better, and seeing space) to understand intelligence and build intelligent systems through visual information processing.
*Illustrative imageSeeing People: Reading the Inner State from Movement
A person's appearance and movements reflect their inner state and thoughts. The lab researches how to understand from vision what people are looking at, what they intend, how they use their bodies to move, and how they influence one another as a group.
*Illustrative imageSeeing Objects: Perceiving Materials and Light
Centered on estimating lighting conditions, reflectance properties, shape, and materials from how objects appear, the lab studies how to extract richer physical and semantic information from the appearance of objects and from scenes.
*Illustrative imageSeeing Better: New Imaging Systems
The lab develops new imaging systems integrated with information processing. Focusing on near-infrared light and light scattering, it has achieved real-time 3D imaging of underwater objects such as swimming fish, as well as imaging of how light travels inside translucent objects.
*Illustrative imageSeeing Space: Understanding the Surrounding Space
To let autonomous vehicles and robots move on their own, the lab designs systems that use cameras and LiDAR to understand the context of the surrounding space. It studies accurate and efficient processing that runs robustly even with limited computing resources.
MembersFaculty
- ProfessorKo Nishino
- Associate ProfessorKen Sakurada
- LecturerRyo Kawahara
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: “Industar I 96 U. USSR lens. img 01” Dmitry Makeev / CC BY-SA 4.0 (cropped)
- Seeing People: Reading the Inner State from Movement: “Estudio de Motion Capture en Funcom” Jesusbella / CC BY-SA 4.0 (cropped)
- Seeing Objects: Perceiving Materials and Light: “Indian pigments” Dan Brady / CC BY 2.0 (cropped)
- Seeing Better: New Imaging Systems: “Fish underwater” Petr Kratochvil / CC0 (cropped)
- Seeing Space: Understanding the Surrounding Space: “BNF Lidar HD” FuzzyGeo / CC BY 4.0 (cropped)
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- Related lab (Spatiotemporal Sensing Lab): “NIMH MEG” Unknown NIMH author / Public domain (cropped)
- Related lab (Integrated Computing Lab): “286 AT motherboard” Mister rf / CC BY-SA 4.0 (cropped)
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