Camera Culture
Technique can capture a scene at multiple depths with one shutter click—no zoom lens needed
Media Tyler PhD students among 14 collegiate inventors awarded the 2018 Lemelson-MIT Student Prize
Guy Satat and Tyler Clites won in the "Drive It!" and "Cure It!" categories, respectively
Developed by MIT researchers, the technology could be a boon for drivers and driverless cars
New 3D camera research from the Media Lab’s Camera Culture group was selected for the Best Papers Special Issue of the ICCV.
He is passionate about developing imaging technologies that solve great challenges in society, science, and health
Spatial resolution, spectral contrast, and occlusion are three major bottlenecks in current imaging technologies for...
Part of a suite of portable projects for eyecare, CATRA is a new way to detect and quantify cataracts. CATRA is a compact eyepiece attach...
Out of (Line of) Sight, But Not Out of View. The Camera Culture group at the Media Lab has created CORNAR: Looking around Corners with Fe...
eyeMITRA allows anyone to easily and non-invasively explore the back of the eye, opening possibilities for new assessments of eye health ...
Technique could lead to cameras that can handle light of any intensity, audio that doesn’t skip or pop.
Computational method improves the resolution of time-of-flight depth sensors 1,000-fold.
Tested with five American cities, Streetchange quantifies the physical improvement or deterioration of neighborhoods.
View past newsletters to get updates on group research, awards, and initiatives:
Machine learning is helping urbanists confirm–or disprove–long-standing theories about cities.
MIT researchers have developed a system that can produce images of objects shrouded by fog so thick that human vision can’t penetrate it.
When a group of forensic dentistry experts set out in 2016 to investigate what may have caused some peculiar holes in a T. rex jaw, they ...
One day, you're a terrible killing and eating machine. Flash forward 65 million years, and you're being conquered by a $150 gaming access...
Ramesh Raskar receives award at ACM SIGGRAPH 2017Raskar, who directs the Camera Culture research group at the MIT Media Lab, is this...
Streetchange uses computer vision and Google Street View to understand urban transformations over time.
The point isn’t to create a new startup, the point is to create a culture of innovation.By Tobi AmosMIT Media Lab
Facebook volunteers and work-at-home moms might be making city planning decisions, thanks to AI research conducted by MIT scientists. Res...
Researchers have used machine learning to quantify the physical improvement or deterioration of neighborhoods in five American cities.
Using computer vision to examine Google Street View, the researchers analyzed how streets and blocks have changed in five American cities.
A recently published paper in the Proceedings of the National Academy of Sciences (PNAS) looks at factors that predict neighborhood change.
System with $150 worth of hardware offers alternative to 3-D scanners that cost 200 times as much
MIT Media Lab researchers have created a quick, simple, and inexpensive way to use mobile phones to measure refractive errors of the eye,...
A conversation with Ramesh Raskar was published as an Impact Spotlight by the Lemelson Foundation. An excerpt is below. ...
Media Ventures: Media Lab Entrepreneurship & Digital Innovations SeminarSandy Pentland, Joost BonsenMedia Lab Entrepreneurship is the...
Ramesh Raskar and the Camera Culture team have been awarded the prestigious Lemelson-MIT Prize which honors outstanding mid-career invent...
Learn more about the Camera Culture group on their group website.
Redefining the camera to exceed the capabilities of the human eye. Achuta’s aim is to build “superhuman visual systems,” which have been ...
It is not so far-fetched that in the near future, a student will work through a difficult vector calculus problem by using his hands to m...