Computer vision

In 2016, MIT CSAIL researchers worked on a range of projects in robotics, theory, wireless technology, software systems, and other disciplines.

Ingestible robots, glasses-free 3-D, and computers that explain themselves

A look at 16 of the coolest things that happened at the Computer Science and Artificial Intelligence Laboratory in 2016.

December 16, 2016

The researchers’ neural network was fed video from 26 terabytes of video data downloaded from the photo-sharing site Flickr. Researchers found the network can interpret natural sounds in terms of image categories. For instance, the network might determine that the sound of birdsong tends to be associated with forest scenes and pictures of trees, birds, birdhouses, and bird feeders.

Computer learns to recognize sounds by watching video

Machine-learning system doesn’t require costly hand-annotated data.

December 2, 2016

Given a still image from a scene, new deep-learning algorithm can create a brief video that simulates the future of that scene.

Creating videos of the future

Given a still image, CSAIL deep-learning system generates videos that predict what will happen next in a scene.

November 29, 2016

Imaging scientist and social impact inventor Ramesh Raskar of MIT is the 2016 recipient of the $500,000 Lemelson-MIT Prize.

Ramesh Raskar awarded $500,000 Lemelson-MIT Prize

Imaging scientist and inventor sets sights on launching peer-to-peer invention platforms for global impact.

September 13, 2016

To simulate objects, MIT CSAIL researchers analyzed video clips to find “vibration modes” at different frequencies that each represent distinct ways that an object can move.

Reach in and touch objects in videos with “Interactive Dynamic Video”

Technique from Computer Science and Artificial Intelligence Lab could improve augmented reality and reduce the need for CGI green-screens.

August 2, 2016

A localizing ground-penetrating radar system from the MIT Lincoln Laboratory complements existing technology, with the goal of achieving safe autonomous vehicles.

Pinpointing vehicles with high precision under adverse weather conditions

MIT Lincoln Laboratory radar system achieves centimeter-level localization; could help driverless cars stay in lane when road markings are obscured.

June 23, 2016

From MIT CSAIL: The left-most column shows the frame before the action begins, with the algorithm's prediction below it. The right columns show the next frames of the video.

Teaching machines to predict the future

Deep-learning vision system from the Computer Science and Artificial Intelligence Lab anticipates human interactions using videos of TV shows.

June 21, 2016

Artificial intelligence produces realistic sounds that fool humans

Video-trained system from MIT’s Computer Science and Artificial Intelligence Lab could help robots understand how objects interact with the world.

June 13, 2016

The goal of MIT's "Duckiebot" class was to create a fleet of 50 self-driving taxis that can navigate the roads of a model city with just a single on-board camera and no pre-programmed maps.

Self-driving cars, meet rubber duckies

“Duckietown” class at Computer Science and Artificial Intelligence Lab teaches autonomy, aims to become global research platform.

April 20, 2016

MIT researchers fed their physics prediction system videos of collisions, shown as screenshots in (a) and (b), which were then converted into simulations generated by the 3-D physics engine, shown in (c) and (d).

Computer model matches humans at predicting how objects move

“3-D physics engine” from the Computer Science and Artificial Intelligence Laboratory simulates the human brain to infer physical properties.

January 4, 2016

For each image, the MemNet algorithm creates a heat map identifying its most memorable and forgettable regions.

Deep-learning algorithm predicts photos’ memorability at “near-human” levels

Future versions of an algorithm from the Computer Science and Artificial Intelligence Lab could help with teaching, marketing, and memory improvement.

December 16, 2015

MIT's Stata Center, which houses the Computer Science and Artificial Intelligence Laboratory

CSAIL joins with Toyota on $25 million research center for autonomous cars

Seeking to reduce traffic casualties, center will focus on robotics and artificial intelligence systems.

September 4, 2015

The autonomous golf carts (shown here) deployed in the Singapore public gardens relied on just a few unobtrusive sensors.

Self-driving golf carts

Autonomous vehicles share sidewalk space with pedestrians in six-day trial in Singaporean public garden.

September 1, 2015

MIT civil and environmental engineering PhD student Justin Chen

Observing invisible vibrations

PhD student Justin Chen magnifies minuscule vibrations in structures to detect damage.

August 27, 2015

MultiFab has been used to print smartphone cases, light-emitting diode lenses, fiberoptic cables, and other items. The printer has a range of applications in consumer electronics, microsensing, medical imaging, and other fields.

“MultiFab” 3-D prints a record 10 materials at once, no assembly required

Printer from Computer Science and Artificial Intelligence Lab uses machine vision and 3-D scanning to self-correct and directly embed components.

August 24, 2015

MIT News | Massachusetts Institute of Technology

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