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from the as-if-Big-Brother-needed-more-bandwidth dept.
Watch Out, MIT’s New AI Model Knows What You’re Doing Behind That Wall:
For better or worse, AI can now figure out what you're doing even without "seeing" you. The MIT Computer Science & AI Lab (CSAIL) has unveiled a neural network model that can detect human actions through walls or in extremely dark places.
Although automating the process of action recognition from visual data has been a computer vision research focus for some time, previous camera-based approaches — much like human eyes — could only sense visible light and were largely limited by occlusions. The MIT CSAIL researchers overcame those challenges by using radio signals in the WiFi frequencies, which can penetrate occlusions.
Their "RF-Action" AI model is an end-to-end deep neural network that recognizes human actions from wireless signals. The model uses radio frequency (RF) signals as input, generates 3D human "skeletons" as an intermediate representation, and can track and recognize actions and interactions of multiple people. The skeleton step enables the model to learn not only from RF-based datasets, but also from existing vision-based datasets.
Researchers say RF-Action is the first model to use radio signals for skeleton-based action recognition. "There are lots of potential applications regarding human behavior understanding and smart homes. For example, monitoring the elderly's abnormal behaviors such as falling down at home, monitoring whether patients take their medicine appropriately, or remote control of smart home devices by actions," says the paper's co-first author Tianhong Li.
Using RF in the "WiFi" bands. 25 hours of data was all it took (or all they collected) to train and test the AI. This article was unclear if the WiFi RF used was active, or passive although earlier reporting specifically mentioned passive.
MIT CSAIL RF Action site has a link to the paper:
Making the Invisible Visible: Action Recognition Through Walls and Occlusions
Tianhong Li*, Lijie Fan*, Mingmin Zhao, Yingcheng Liu, Dina Katabi
International Conference on Computer Vision (ICCV), 2019
[PDF] [arXiv] [BibTeX]
This looks like an update of the story we first published in 2015, but now including AI.
Previously:
- X-Ray Vision? Technology Making It a (Sort-of) Reality for $300
- See Through Walls by Passive Radiation From Wi-Fi
(Score: 2) by jmichaelhudsondotnet on Monday October 14 2019, @04:34PM
Idk maybe I was writing in a way to sound like I know more than I did, I can do better. Overstating, using bigger scoped words than necessary, I have had trouble with this in the past.
So easy to do until someone rolls by who knows more.