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I'm REALLY unclear how you decided to post this giraffe comment... The picture and the words in the article show cameras next to the rear view mirror. """ Usi

I'm REALLY unclear how you decided to post this giraffe comment... The picture and the words in the article show cameras next to the rear view mirror. """ Using two inexpensive cameras on either side of a vehicle’s windshield, Cornell researchers have discovered they can detect objects with nearly LiDAR’s accuracy and at a fraction of the cost."""

gamblor956 7y ago
That's not what the article originally said, so it appears that it's been updated since then. Good think I quoted the relevant section of the article in my comment... That being said, existing self-driving cars already have some cameras at that level without displaying the sort of accuracy the researchers found, which relates to the methodology issues other commenters have noted.
- DennisP 7y ago
  The researchers described a new way of processing the data, claiming a dramatic improvement over previous methods.
  - gamblor956 7y ago
    In accuracy, over existing visual systems, but still worse than LIDAR and at the cost of several processing-intensive intermediate steps. In any conceivable situation where you'd use this, it would actually be better to just use LIDAR.
- WhatIsDukkha 7y ago
  That quote I posted was the sentences just before the ones you selected. Why don't you read the paper a bit - https://arxiv.org/pdf/1812.07179.pdf https://arxiv.org/pdf/1812.07179.pdf And then work out why they used the words "birds eye" that you found so upsetting.
  - gamblor956 7y ago
    Thanks for the paper. I actually agree with those complaining about the methodology of the paper and if anything, having read the article I agree it even more strongly states why LIDAR is essential for the foreseeable future. The research paper, in a nutshell, was about transforming stereovisual images to psuedo-birds eye data, like roof-mounted LIDAR. This, theoretically, would result in about a 350% improvement over current vision-based methods...but still only 50% of that of existing LIDAR systems. In exchange, you just have to 1) convert the stereovisual data to a 3d point cloud, 2) transform the point cloud to birds-eye perspective, and 3) run the LIDAR systems on the point cloud, and 4) do that all in milli-seconds.

gamblor956 7y ago

That's not what the article originally said, so it appears that it's been updated since then. Good think I quoted the relevant section of the article in my comment... That being said, existing self-driving cars already have some cameras at that level without displaying the sort of accuracy the researchers found, which relates to the methodology issues other commenters have noted.

DennisP 7y ago
The researchers described a new way of processing the data, claiming a dramatic improvement over previous methods.
- gamblor956 7y ago
  In accuracy, over existing visual systems, but still worse than LIDAR and at the cost of several processing-intensive intermediate steps. In any conceivable situation where you'd use this, it would actually be better to just use LIDAR.
WhatIsDukkha 7y ago
That quote I posted was the sentences just before the ones you selected. Why don't you read the paper a bit - https://arxiv.org/pdf/1812.07179.pdf https://arxiv.org/pdf/1812.07179.pdf And then work out why they used the words "birds eye" that you found so upsetting.
- gamblor956 7y ago
  Thanks for the paper. I actually agree with those complaining about the methodology of the paper and if anything, having read the article I agree it even more strongly states why LIDAR is essential for the foreseeable future. The research paper, in a nutshell, was about transforming stereovisual images to psuedo-birds eye data, like roof-mounted LIDAR. This, theoretically, would result in about a 350% improvement over current vision-based methods...but still only 50% of that of existing LIDAR systems. In exchange, you just have to 1) convert the stereovisual data to a 3d point cloud, 2) transform the point cloud to birds-eye perspective, and 3) run the LIDAR systems on the point cloud, and 4) do that all in milli-seconds.