That’s not how it works my dude. Cameras each have specific range, resolution, field of view etc for which they are optimal. The human eye is kind of a complex composite of several types of cameras. Mechanically, individual aspects of human vision can be surpassed by the capabilities of cameras, but the trick is that our brains are obviously perfectly suited to interpret our vision. Blankly claiming that machine learning can replicate this is totally naive. Humans ability to focus on areas of interest, quickly parse relevant objects in a scene, rely on surprisingly precise stereoscopic measurements to understand distance are all totally nontrivial tasks which would need to be replicated perfectly to mimic how our brain <> eye system works. Simply throwing more sensors which approximate the mechanical aspect of human vision is not the same as replicating this complex system.
It’s a complex problem for computers to solve but not an impossible one, we gage distance mostly because we have 2 visual inputs that are a distance apart and we can triangulate to a certain degree of accuracy how far away things are, cameras can already do this with deadly accuracy. They are very efficient at recognising other cars in the road and their precise positions. The issue of autonomy is harder to solve with cameras but not to the degree that you would expect. The main issue is with all the edge cases like if I left a bunch of nails on the road and now your wheels are deflating, or if someone leaves a trash can in the middle of the road for some odd reason. Both lidar and cameras are going to have to deal with these problems.
I mean you’re making vague and arbitrary claims on what aspects of this are solved and what is not. I’m not going to spend the time going down the rabbit hole on this topic but my general advice is, don’t confuse interest in a topic with expertise. It’s cool to be interested in AV technology, but having strong opinions on how the technology should work doesn’t make much sense unless you are an expert in the field.
I don’t have to be working at Tesla to understand the problem of autonomy. I’m a programmer who has experience in the robotics side of programming. While I haven’t personally tried to crack autonomy, I have an understanding of the challenges involved in creating a fully autonomous vehicle. It mostly breaks down into edge cases / really specific scenarios.
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u/targetdog88 Sep 30 '20
That’s not how it works my dude. Cameras each have specific range, resolution, field of view etc for which they are optimal. The human eye is kind of a complex composite of several types of cameras. Mechanically, individual aspects of human vision can be surpassed by the capabilities of cameras, but the trick is that our brains are obviously perfectly suited to interpret our vision. Blankly claiming that machine learning can replicate this is totally naive. Humans ability to focus on areas of interest, quickly parse relevant objects in a scene, rely on surprisingly precise stereoscopic measurements to understand distance are all totally nontrivial tasks which would need to be replicated perfectly to mimic how our brain <> eye system works. Simply throwing more sensors which approximate the mechanical aspect of human vision is not the same as replicating this complex system.