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Old Today, 10:11 AM   #121
GlennB
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Originally Posted by Dr. Keith View Post
Do you think humans are better at recognizing vehicles than computers?

I had dinner with four people who were involved in a hit run yesterday. One said it was a truck, the second said it was a Hummer, the third said "it looked like that" while pointing at an FJ cruiser and the fourth only knew that the girl driving had her phone out.

I trust a computer to differentiate between a Ford Transit Connect and a Ford Transit more reliably than most humans.
I wasn't talking about recognising the vehicle, just gauging its size. And we were also talking about the Tesla which has only one camera on each central pillar looking sideways. With no range sensor the image it sees is of little use except to say 'there's something down the road that looks like a vehicle, and its getting bigger/smaller'.

As discussed subsequently, the Tesla 3 'brochure' seems to be a rehash of their assisted freeway driving system, with many added promises that totally depend on better software and (imo) different/more sensors. Note that they're not offering equipment upgrades or add-ons, just software.
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Old Today, 10:54 AM   #122
Horatius
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Originally Posted by GlennB View Post
I wasn't talking about recognising the vehicle, just gauging its size. And we were also talking about the Tesla which has only one camera on each central pillar looking sideways. With no range sensor the image it sees is of little use except to say 'there's something down the road that looks like a vehicle, and its getting bigger/smaller'.

And again, you're ignoring what I've said about that.

With decent imaging analysis, knowledge of the characteristics of the camera, and a database of information on typical vehicles, determining the range is trivial. Here's one ridiculously simple algorithm:
  1. Image analysis IDs an oncoming vehicle, and its relative orientation
  2. Database look up tells us the dimensions of the vehicle
  3. How many pixels wide the image is tells us what angle the vehicle subtends
  4. basic trig with the known vehicle dimensions and the measured angular extent tells us how far away it is.


How long that process takes is really only dependent on the speed of the processor, which again, is never going to get worse than it is today. If/when we get to the point that this can be done at a typical video frame rate of 30fps (if we're not at that point now), it will be trivial to implement this.
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Old Today, 12:34 PM   #123
GlennB
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Originally Posted by Horatius View Post
And again, you're ignoring what I've said about that.

With decent imaging analysis, knowledge of the characteristics of the camera, and a database of information on typical vehicles, determining the range is trivial. Here's one ridiculously simple algorithm:
  1. Image analysis IDs an oncoming vehicle, and its relative orientation
  2. Database look up tells us the dimensions of the vehicle
  3. How many pixels wide the image is tells us what angle the vehicle subtends
  4. basic trig with the known vehicle dimensions and the measured angular extent tells us how far away it is.


How long that process takes is really only dependent on the speed of the processor, which again, is never going to get worse than it is today. If/when we get to the point that this can be done at a typical video frame rate of 30fps (if we're not at that point now), it will be trivial to implement this.
Definitely not ignored, because I've been following your posts, and also the word 'subtend' really gets my attention and I even know what it means (parsecs might be involved ). In case I simply missed it I checked all your posts, and it doesn't seem to relate to the various cases in that pdf the other day. (o/t, but searches of this thread returned no matches even for some of the words you clearly typed, so what's going on with that I don't know.)

Anyway ... vehicle make+model recognition - right. Not so easy if the car is coming down a hill or (worse?) over the brow of a hill. Maybe a bugger if it's a similar colour to a complex background. Vehicle covered in grime? How about "it's night time", or the sun is in the lens (didn't that bad Tesla accident have something to do with low sun straight ahead?) ? Does lidar care about all that?

In my daily doings I frequently have to make a turn with my vision partly obscured by some moron who has parked on the verge yards from the junction where I'm waiting. Anecdotal, but true. I can see the tops of cars approaching but I doubt if any s/w could identify the cars.

But the crucial question for me is: "Why is every other bugger in the field going for radar/lidar, while Tesla claim to be able to do much of this with optics?" I said it upthread but I'll say it again - I believe they're just repackaging their 'drive assist' technology with plausible deniability when the fancy bits can't actually be delivered.

p.s. Out of interest this is, I believe the side camera on the Tesla 3
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Old Today, 12:52 PM   #124
Dr. Keith
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Originally Posted by GlennB View Post
I wasn't talking about recognising the vehicle, just gauging its size.
I'd still trust a computer with a single camera to gauge the size of a transit connect vs. a transit much more quickly and accurately than the average human. Same with speed and change in speed.
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Old Today, 01:16 PM   #125
GlennB
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Originally Posted by Dr. Keith View Post
I'd still trust a computer with a single camera to gauge the size of a transit connect vs. a transit much more quickly and accurately than the average human. Same with speed and change in speed.
At night?
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Old Today, 01:23 PM   #126
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Originally Posted by GlennB View Post
At night?
Why not? Are humans really good at telling vehicles apart at night?
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Old Today, 02:03 PM   #127
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Originally Posted by GlennB View Post
At night?


I recently installed a back up camera in my truck, and the scene shown in the dashboard screen is noticeably brighter than what I see in my mirrors, or even just out the windows. Low light camera technology is also a thing.
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