A team of computer scientists has developed a new system that recognizes near-keyboard hand gestures to expand laptop interaction.
The new technology is an innovation in the field of human-computer interaction and allows users to give commands that would otherwise involve keyboard shortcuts or mouse round-trips.
Known as Typealike, the system was created by a team of researchers at the Cheriton School of Computer Science — Nalin Chhibber, a recent master’s graduate, Hemant Surale, a recent PhD graduate, Fabrice Matulic, a recent postdoctoral researcher, and Professor and Cheriton Faculty Fellow Daniel Vogel.
“It started with a simple idea about new ways to use a webcam,” said Nalin. “The webcam is pointed at your face, but the most interaction happening on a computer is around your hands. So, we thought, what could we do if the webcam could pick up hand gestures?”
The initial insight led to the development of a small mechanical attachment that redirects the webcam downwards towards the hands. The team then created a software program capable of understanding distinct hand gestures in variable conditions and for different users. The team used machine learning techniques to train the Typealike program.
“It’s a neural network, so you need to show the algorithm examples of what you’re trying to detect,” said Fabrice. “Some people will make gestures a little bit differently, and hands vary in size, so you have to collect a lot of data from different people with different lighting conditions.”
The team recorded a database of hand gestures with dozens of research volunteers. They also had the volunteers do tests and surveys to help the team understand how to make the program as functional and versatile as possible.
“We’re always setting out to make things people can easily use,” Professor Vogel said. “People look at something like Typealike, or other new tech in the field of human-computer interaction, and they say it just makes sense. That’s what we want. We want to make technology that’s intuitive and straightforward, but sometimes to do that takes a lot of complex research and sophisticated software.”
Please also see Nalin Chhibber, Hemant Bhaskar Surale, Fabrice Matulic, and Daniel Vogel. 2021. Typealike: Near-Keyboard Hand Postures for Expanded Laptop Interaction. Proceedings of the ACM on Human-Computer Interaction 5, ISS, Article 486 (November 2021), DOI: https://doi.org/10.1145/3486952.
This research received a Best Paper Honorable Mention Award at ACM ISS 2021.