Machine learning metrics are tricky; if you don't know what they mean, they tend to sound impressive, when they really aren't. 94% accuracy is actually terrible, to the point where I would call this a scam if it looked like it was being marketed B2B. Consider: If some company has a database with a million people in it, and this technology rules out 94% of possibilities, then this puts you in a group of 60,000 people. This is about the same accuracy is they'd get if they just measured your height, and ruled out everyone more than an inch shorter or taller than you. (In fact, I'd put pretty high odds on this being exactly what the "gait recognition" neural network is actually doing.) So it might work as a cross-check in combination with some other tracking technology (eg your phone's MAC address), but if that happens, it's the other tracking technology you should be focusing on.
As an ML practitioner, that's not what I'd mean if I said "94% accurate". I would mean that the label was correct 94% of the time. This is very much affected by the size of the db -- that is probably why the use a weaselly phrase "can reach" -- "The average recognition rate can reach 94.1%" says the Watrix link.
This is a good point concerning current gait recognition technology. However, I don't doubt it will improve. On longer timescales, this should happen naturally as compute gets cheaper and more data gets collected. On shorter timescales, this can be accelerated using techniques such as synthetic data generation.
Perhaps there is a natural limit to gait recognition, if it turns out that people can't be uniquely identified from their gait, even in the limit of perfect data. But if there isn't, then in 10 years, "94%" will turn into "99.999%", or whatever...
Given that most shoppers in Western grocery stores currently carry mobile phones that tell anyone who's nearby about their identity. There's little need to use anything else to identity shoppers.
I had an experience where a friend changed her body tension patterns enough that I didn't recognize her after she was a week on vacation.
Physical therapy to be able to switch walking styles deliberately might be problematic because having the ability to move in a very conscious way is likely to produce tells. Whether or not the gait recognition algorithm can pick up on them however is another question and probably not at the level of only giving 94% accuracy.
Japan, the US, and the UK have also been working on gait recognition, though I doubt it's being seriously deployed in the same way as in China.
A decade ago the London was of the mindset that the limiting factor for their surveilance was disc space.
I would be surprised if the Five Eyes don't have gait recognition.
This video on how Usonian CIA operatives disguise themselves claims a simple piece of gravel in your shoe will change how you walk completely: https://youtu.be/JASUsVY5YJ8
The big problem I see with all of the methods you describe to avoid matching is that they are one-offs. A mask obscures your identity; you are attempting to make your face indistinguishable from anyone else's. But alterations like (most of ) the ones you describe just create a separate identity -- more akin to plastic surgery. This is great if you are trying to avoid linking yourself to a former identity, but not as useful for trips to the grocery store, where this new ID will be tracked and monetized.
My suggestion would be to wear something that hides your gait, rather than alters it. A burqa might work. Or ride in the motorized cart.
Regarding the goal: Personally, I find the tracking by the grocery store helpful enough (given the incentives they set up) that this is among my areas of least concern for tracking. I appreciate, for example, having novel grocery products that I might like suggested. This is different than for, say, televisions, where I discover that I am artificially dissatisfied by learning about newer features. A key differentiator is that I am constantly buying new food, so there is no pressure to buy something vs. remain satisfied with something I already own. Of course, other areas where gait tracking would come into play might provide a different value profile for me.
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Gait recognition technology ( = identifying a person by the way they walk) is getting good, and I find this trend unnerving.
Current context: It's already deployed in China by a company called Watrix, which claims 94% accuracy up to 50 meters away from any angle. Japan, the US, and the UK have also been working on gait recognition, though I doubt it's being seriously deployed in the same way as in China.
And it will only get better. Here is a recent paper out of Zhejiang University in which they generate synthetic data for training gait recognition systems (import AI 252 summary here).
What makes me uneasy is the supposed robustness of gait recognition technology:
“You don’t need people’s cooperation for us to be able to recognize their identity,” Huang said in an interview in his Beijing office. “Gait analysis can’t be fooled by simply limping, walking with splayed feet or hunching over, because we’re analyzing all the features of an entire body.” ~ AP News article [Note Huang is the CEO of Watrix]
Main question: In the future, if my local grocery store installs cameras and uses facial recognition technology to track my purchases and show me targeted ads, I can probably prevent this by wearing a face covering. What's the analogy here for gait recognition—how do I make myself confusing and/or undetectable to such systems?
Some random ideas I had:
I'm thinking about mostly with the "lazy surveillance" use case in mind, which is what I consider to be the most likely outcome in the western world. For example, I am subjected to "lazy surveillance" by Facebook/Google/other tech companies, but I can circumvent this by using a VPN, incognito window, different accounts / locations, etc. Hence the motivating example of the grocery store—a low stakes but realistic future scenario.