Researchers at the University of Texas at San Antonio developed a model that can track the movement of the shoulders and arms of a person typing during a video call, to determine what they are typing.
The person's movements are mapped onto a keyboard using optical flow, and the results are cross-referenced against a dictionary of commonly typed words.
The model correctly identified the word being typed 75% of the time, though its success rate varies based on a user's typing skills.
For instance, the model correctly identified 83% of words typed by those who "peck" at the keyboard.
Further, 3.4% more words were recovered on Skype calls than on Zoom calls, possibly due to the way each app compresses video.
The university's Murtuza Jadliwala said users can protect their privacy by blurring their backgrounds, skipping frames in the video, and pixelating their shoulders and arms.
From New Scientist
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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