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It isn't necessary. As you suggest, humans have only normal eyes, not laser eyes, and we still manage to drive. Yes and no. It's also just nice to have more di
by ebg13 7y ago
It isn't necessary. As you suggest, humans have only normal eyes, not laser eyes, and we still manage to drive.
Yes and no. It's also just nice to have more different kinds of data available. Just because humans don't have laser eyes doesn't mean we can't try to do better than that.
Depth from stereo is not ML, but yes.
- StavrosK 7y agoIt isn't "necessary" for small values of "necessary", ie if you have a human brain hooked up to human eyes. It is extremely necessary if you only have a computer and some primitive software, like we do now, as in "self-driving won't work as well otherwise".
- herogreen 7y agoYet depth from stereo is, to some extent, AI because the matching of pixels that corresponds to the same physical point is not trivial and uses heuristics.
- Animats 7y agoDepth from stereo gets worse at distance, while LIDAR and RADAR read depth directly.
- mlyle 7y ago> Depth from stereo is not ML, but yes. Tesla in particular, and others are moving towards getting depth from ML. Yes, you can do dumb coincidence-finding, but there's a lot of corner cases (leafy objects, specular reflections, etc) that screw this up. Humans don't just use coincidence finding, but use all kinds of other clues (size, texture gradients, monocular parallax, shadows, linear perspective, attenuation from haze, etc) to infer depth.
- tyfon 7y agoTesla is using data from the radar to annotate the images from the cameras with distance before running it through the ML training, but for driving it is using a combination of all (stereo vision, ML and radar) to produce the final number. The human neural network is of course fine tuned to this and my father who is blind on one eye will actually move his head sideways a bit to judge distance when he is driving :)
- mlyle 7y agoYah. Waymo is doing the same with the lidar, which provides both higher accuracy and higher resolution "ground truth" distance data. And yes, everyone uses sensor fusion and filtering, not just "ML".
- ebg13 7y ago> Humans don't just use coincidence finding Maybe not just, but we do use it, except we do it by converging our eyes for _actual_ coincidence within a small focal center instead of ambiguous coincidence everywhere in the field of view like CV stereo typically tries to do. Gimbaled cameras that (metaphorically speaking, of course) "look" where drivers are supposed to look with an attention model instead of being statically coplanar could do this too.
- mlyle 7y ago> except we do it by converging our eyes for _actual_ coincidence within our focal center instead of ambiguous coincidence everywhere in the field of view. Only at very close range. That's convergence, and mostly a 5m and less phenomenon (not so relevant at driving ranges).
- visarga 7y ago> we still manage to drive not amazingly well, though, because there are millions of victims each year SDCs are supposed to be better than us, so more sensors make sense.
- rimliu 7y agoI'd argue that the majority of victims are the result of humans suppressing their judgment. E.g. not because a human was incapable to drive safely, but purposedly chose to drive unsafely: overtake where it is limited visibility, speeding when conditions do not allow for it.
- kohtatsu 7y agoAttention-related crashes are likely a good chunk as well. Also unsafe lefts and ran/stale lights. That's probably most all of them between our comments.