“You come on any time,” Benkendorf said from Sunrise, Fla. “I’ve got a dog you can play with. I’ve got a spare room. Anytime you need a vacation. If they close you down again, Stacie, you’re welcome.”
Weldon and Benkendorf have never met in-person, but over the past four months they’ve developed a friendship after matching with each other on a website. Quarantine Buddy, founded by two Cornell University students in April, matches people from around the world based on their background and interests, and they meet virtually.
The website has helped more than 50,000 people — spanning all 50 U.S. states and more than 100 countries — build friendships while stuck at home.
“We kind of realized how lonely and isolating this can be for so many people,” said Jordyn Goldzweig, a Quarantine Buddy co-founder. “The pandemic itself really brought out the fact that a lot of people are isolated, and even though we have technology, people aren’t utilizing it to meet other people. We really wanted to do our part.”
In March, Goldzweig and co-founder Sam Brickman left Cornell for their respective New Jersey and New York homes due to the coronavirus outbreak. A few weeks later, the junior computer science majors met with one of their professors, Pam Silverstein, on Zoom. After discussing a project, Silverstein expressed how thankful she was to speak with someone, because she hadn’t left her house in about a week.
Goldzweig and Brickman have worked on multiple projects together, including an application last year called “Zing” that connects classmates. They expanded that idea to assist people in situations such as Silverstein’s.
They spent two all-nighters shaping the website, staying awake on coffee and electronic dance music. They created a survey with nine questions that allows users to customize what they are looking
Researchers from Cornell University have created an earphone system that can track a wearer’s facial expressions even when they’re wearing a mask. C-Face can monitor cheek contours and convert the wearer’s expression into an emoji. That could allow people to, for instance, convey their emotions during group calls without having to turn on their webcam.
“This device is simpler, less obtrusive and more capable than any existing ear-mounted wearable technologies for tracking facial expressions,” Cheng Zhang, director of Cornell’s SciFi Lab and senior author of a paper on C-Face, said in a statement. “In previous wearable technology aiming to recognize facial expressions, most solutions needed to attach sensors on the face and even with so much instrumentation, they could only recognize a limited set of discrete facial expressions.”
The earphone uses two RGB cameras that are positioned below each ear. They can record changes in cheek contours when the wearer’s facial muscles move.
Once the images have been reconstructed using computer vision and a deep learning model, a convolutional neural network analyzes the 2D images. The tech can translate those to 42 facial feature points representing the position and shape of the wearer’s mouth, eyes and eyebrows.
C-Face can translate those expressions into eight emoji, including ones representing neutral or angry faces. The system can also use facial cues to control playback options on a music app. Other possible uses include having avatars in games or other virtual settings express a person’s actual emotions. Teachers might be able to track how engaged their students are during remote classes too.
Due to the impact of COVID-19, the researchers could only test C-Face with nine participants. Still, the emoji recognition was more than 88 percent accurate and the facial cues more than 85 percent accurate. The researchers found the earphones’ battery capacity