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Comment by syntaxing | Hacker News Reader

This is true because they use cameras and camera lack depth information despite it being used with “state of the art AI”. This would not be an issue if they have any real depth based measurement system like a LiDAR.

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How hard is it to use multiple cameras to gauge depth perception, as per human binocular vision?

(Serious question, I know nil about machine vision)

It's well understood to be impossible / not there yet, the argument then shifts to "but ML is awesome so it could happen?" to which the correct response is "anything is possible but we're nowhere close"

In some ways, it can be better than lidar. The colour signal can be perfectly matched with the depth signal to provide further context. This is particularly useful for tracking moving objects. Vision-based systems also have a far greater resolution, especially when additional cameras are added.

But having both would be best. The drawbacks of camera are additional compute being necessary for stitching and the risk of occlusions occurring due to something like adverse weather conditions. It also only offers a calculated estimation rather than a true distance measurement.

It’s extremely difficult, the biggest issue is that any vision based depth system is so damn noisy.

Do Teslas have 2 main forward cameras? I know that Subarus do as you can see them

https://www.thetruthaboutcars.com/2012/03/subaru-uses-stereo...

Related, why is rangefinding like on rangefinder cameras not usable?

1. videos: https://www.lensangle.com/how-do-rangefinder-cameras-work/

2. a photo or two: https://www.howtogeek.com/365801/what-is-a-rangefinder-camer...

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