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That's mostly spin too. You want a strategy that works well enough, because that's the regime we live in currently. Other human drivers certainly aren't imple

by ajross 3y ago

That's mostly spin too. You want a strategy that works well enough, because that's the regime we live in currently. Other human drivers certainly aren't implementing a LIDAR-based sensor fusion strategy and you have to share the roads with them. Your algorithm for evaluating their safety is "how likely are they to kill you" and not an absolutist position on the specific equipment in their heads or cars, and you're clearly OK with that. As far as LIDAR itself: sure, yeah, you get depth info out of it. But depth info is only part of the problem, and frankly it's clear at this point that it's one of the easiest. The hard parts are in the recognition side: not "is that pedestrian in your path" (easy), but "is that pedestrian going to step into the street or not" (hard). And that's a computer vision problem. You can use LIDAR output as vision input, sure, but it's has no advantages. Tesla was right, basically.

BugsJustFindMe 3y ago
> But depth info is only part of the problem, and frankly it's clear at this point that it's one of the easiest. That's proven false by the cars continuing to drive into stationary objects. This failure mode is not ambiguous. Camera input is garbage for interpreting geometry, especially from very smooth or very discontinuous surfaces, and especially with the shitty low resolution and low dynamic range cameras they use, and especially with non-stereoscopic cameras with no motion freedom relative to the vehicle body. Lidar is a necessary crutch for working around the fact that, while hypothetical cameras that don't exist might work well, all available cameras are unsuitable for the purpose, and calculating multi-view geometry accurately costs time. > The hard parts are in the recognition side: not "is that pedestrian in your path" (easy), but "is that pedestrian going to step into the street or not" (hard). And that's a computer vision problem. Pedestrian motion is not strictly a vision challenge but a general category of environment understanding (mass, momentum, motion mechanics). Vision is only one possible input mode preliminary to modeling.
- ajross 3y ago
  > That's proven false by the cars continuing to drive into stationary objects. It has? This again gets to "are they safer than human drivers?", because the competition hits stationary objects all the time. If you have data let's discuss data, but "proven false" is, again, just spin. > Pedestrian motion is not strictly a vision challenge but a general category of environment understanding Semantic evasion. You agree that it's "not a problem solved by LIDAR", right? It needs a camera. You can use a LIDAR output as a (somewhat inferior) camera, but it's not providing any advantages.
  - BugsJustFindMe 3y ago
    > "But depth info is...one of the easiest [problems]" ... "are they safer than human drivers?" ... Semantic evasion. It looks like you're jumping from "depth is easy with cameras" (demonstrated false) to "safer than humans anyway without it" (speculative and not demonstrated by anyone), so who here is evading? That they're safer is not demonstrated. That depth is easy with just cameras is demonstrated to be false by the continuing failures in the presence of extreme financial incentive to not have those failures. > You agree that it's "not a problem solved by LIDAR", right? It needs a camera. You can use a LIDAR output as a (somewhat inferior) camera, but it's not providing any advantages. The LIDAR addresses the part where all current cameras are unsuited to mapping physical world geometry under driving conditions. It's not one or the other, but you appear to be assuming an imaginary not-the-one-we-live-in reality where only one is needed because you assume that all available cameras aren't actually very bad. But they are all actually very bad. So we continue to need both for the indeterminate future until someone invents mechanically robust extreme fidelity stereoptic cameras with motion freedom independent from the vehicle body, which is what humans use. Humans are unsafe predominantly because of inattention, not ability. Camera-only vehicles are unsafe because of camera ability before you even get to the attention part. Tesla's repeated failures over the years (and your conviction toward what Tesla is doing regardless) demonstrate a dangerously erroneous belief that object identification is the first and most important step for path planning. But that's not how humans drive, and it's not how to drive safely. The vehicle should avoid driving into any space that isn't going to be open smooth road, period, so the most important step is mapping geometry. There are no cameras currently suited for that. This is not a theoretical limitation. Just a practical one. Becoming suitable with current cameras would require many more cameras with much more processing per frame, so if you're trying to save costs vs lidar, you won't.
andbberger 3y ago
> Other human drivers certainly aren't implementing a LIDAR-based sensor fusion strategy and you have to share the roads with them humans are absolutely doing sensor fusion, brains are bayesian inference machines. do not underestimate the power of the visual system. and no, that the brain does is not an argument in favor of LIDAR-less cars. the eyeball + visual cortex system is alien technology compared to our feeble models. beware the hubris of a man who has learned to classify golden retrievers.
- ajross 3y ago
  > humans are absolutely doing sensor fusion, brains are bayesian inference machines. do not underestimate the power of the visual system. Not in the sense in the upthread comment they aren't, no. We have two cameras and two microphones. The latter is limited to weak detection of horns and tire screeches and not much else, and the former are too close together to give stereoscopic depth information at traffic distances. We have a camera, basically. We do lots of stuff with the camera, sure. But that's not sensor fusion. We sure as hell don't have anything like LIDAR.
  - BugsJustFindMe 3y ago
    > the former are too close together to give stereoscopic depth information at traffic distances They're only too close together to give very precise depth information, but they do still provide useful depth information. They also double the incoming light and SNR, which is why the average person performs better on visual acuity tests with both eyes than with only one or the other. > We have a camera, basically. We do lots of stuff with the camera, sure. But that's not sensor fusion. They're varifocal cameras with very good dynamic range that receive double the light input and that also have full freedom to move around, both rotationally and translationally, which provides, among other things, more depth information and better object boundary segmentation from controlled parallax and focus, and which involves the continuously varied activation of many different muscles and sensory nerves because they're attached to the extremely complex and sensitive proprioceptive structure called the rest of your body, which your brain fully uses as input when processing visual information. And we know that your brain uses this other information, because not having this other information causes reduced perception and motion sickness. So, no, they're not just cameras. And, yes, we do sensor fusion.

by ajross 3y ago

BugsJustFindMe 3y ago

> But depth info is only part of the problem, and frankly it's clear at this point that it's one of the easiest. That's proven false by the cars continuing to drive into stationary objects. This failure mode is not ambiguous. Camera input is garbage for interpreting geometry, especially from very smooth or very discontinuous surfaces, and especially with the shitty low resolution and low dynamic range cameras they use, and especially with non-stereoscopic cameras with no motion freedom relative to the vehicle body. Lidar is a necessary crutch for working around the fact that, while hypothetical cameras that don't exist might work well, all available cameras are unsuitable for the purpose, and calculating multi-view geometry accurately costs time. > The hard parts are in the recognition side: not "is that pedestrian in your path" (easy), but "is that pedestrian going to step into the street or not" (hard). And that's a computer vision problem. Pedestrian motion is not strictly a vision challenge but a general category of environment understanding (mass, momentum, motion mechanics). Vision is only one possible input mode preliminary to modeling.

ajross 3y ago
> That's proven false by the cars continuing to drive into stationary objects. It has? This again gets to "are they safer than human drivers?", because the competition hits stationary objects all the time. If you have data let's discuss data, but "proven false" is, again, just spin. > Pedestrian motion is not strictly a vision challenge but a general category of environment understanding Semantic evasion. You agree that it's "not a problem solved by LIDAR", right? It needs a camera. You can use a LIDAR output as a (somewhat inferior) camera, but it's not providing any advantages.
- BugsJustFindMe 3y ago
  > "But depth info is...one of the easiest [problems]" ... "are they safer than human drivers?" ... Semantic evasion. It looks like you're jumping from "depth is easy with cameras" (demonstrated false) to "safer than humans anyway without it" (speculative and not demonstrated by anyone), so who here is evading? That they're safer is not demonstrated. That depth is easy with just cameras is demonstrated to be false by the continuing failures in the presence of extreme financial incentive to not have those failures. > You agree that it's "not a problem solved by LIDAR", right? It needs a camera. You can use a LIDAR output as a (somewhat inferior) camera, but it's not providing any advantages. The LIDAR addresses the part where all current cameras are unsuited to mapping physical world geometry under driving conditions. It's not one or the other, but you appear to be assuming an imaginary not-the-one-we-live-in reality where only one is needed because you assume that all available cameras aren't actually very bad. But they are all actually very bad. So we continue to need both for the indeterminate future until someone invents mechanically robust extreme fidelity stereoptic cameras with motion freedom independent from the vehicle body, which is what humans use. Humans are unsafe predominantly because of inattention, not ability. Camera-only vehicles are unsafe because of camera ability before you even get to the attention part. Tesla's repeated failures over the years (and your conviction toward what Tesla is doing regardless) demonstrate a dangerously erroneous belief that object identification is the first and most important step for path planning. But that's not how humans drive, and it's not how to drive safely. The vehicle should avoid driving into any space that isn't going to be open smooth road, period, so the most important step is mapping geometry. There are no cameras currently suited for that. This is not a theoretical limitation. Just a practical one. Becoming suitable with current cameras would require many more cameras with much more processing per frame, so if you're trying to save costs vs lidar, you won't.

andbberger 3y ago

> Other human drivers certainly aren't implementing a LIDAR-based sensor fusion strategy and you have to share the roads with them humans are absolutely doing sensor fusion, brains are bayesian inference machines. do not underestimate the power of the visual system. and no, that the brain does is not an argument in favor of LIDAR-less cars. the eyeball + visual cortex system is alien technology compared to our feeble models. beware the hubris of a man who has learned to classify golden retrievers.

ajross 3y ago
> humans are absolutely doing sensor fusion, brains are bayesian inference machines. do not underestimate the power of the visual system. Not in the sense in the upthread comment they aren't, no. We have two cameras and two microphones. The latter is limited to weak detection of horns and tire screeches and not much else, and the former are too close together to give stereoscopic depth information at traffic distances. We have a camera, basically. We do lots of stuff with the camera, sure. But that's not sensor fusion. We sure as hell don't have anything like LIDAR.
- BugsJustFindMe 3y ago
  > the former are too close together to give stereoscopic depth information at traffic distances They're only too close together to give very precise depth information, but they do still provide useful depth information. They also double the incoming light and SNR, which is why the average person performs better on visual acuity tests with both eyes than with only one or the other. > We have a camera, basically. We do lots of stuff with the camera, sure. But that's not sensor fusion. They're varifocal cameras with very good dynamic range that receive double the light input and that also have full freedom to move around, both rotationally and translationally, which provides, among other things, more depth information and better object boundary segmentation from controlled parallax and focus, and which involves the continuously varied activation of many different muscles and sensory nerves because they're attached to the extremely complex and sensitive proprioceptive structure called the rest of your body, which your brain fully uses as input when processing visual information. And we know that your brain uses this other information, because not having this other information causes reduced perception and motion sickness. So, no, they're not just cameras. And, yes, we do sensor fusion.