Tesla Cars That Crash Explain Why Smartphone Bokeh Is So Unreliable

Started Aug 6, 2019 | Discussions thread
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FluidKnowledge Regular Member • Posts: 498
Tesla Cars That Crash Explain Why Smartphone Bokeh Is So Unreliable
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I just saw this ArsTechnica that talks about why Tesla "self driving" sensors are so bad and realized that it perfectly explains why smartphone bokeh is so unreliable and looks so bad. Both Tesla Cars and most smartphones use dual cameras to estimate depth by the parallax effect but there is significant problems with this method where the depth estimates can be wildly unreliable due to a number of optical issues such as texture, reflections, and occlusion.

This all makes sense now. It explains why Tesla cars keep crashing into the side of semi-trailers (possibly due to low textures and Tesla intentionally disabling stopping for objects on the road) and why smartphone bokeh keeps blurring out the wrong things or not blurring out things it should (like occlusions between armpits or occluded gaps between the hair and head). The parallax method is inherently broken if you want reliability and accuracy.

Quote from the article below:

https://arstechnica.com/cars/2019/08/elon-musk-says-driverless-cars-dont-need-lidar-experts-arent-so-sure/2/

This technique only works if the software correctly matches a pixel in one image with the corresponding image in the other image. If the software gets this wrong, then distance estimates can be wildly off.

It's not a trivial problem. In their 2018 paper, the National Chiao Tung University researchers explained that it is "difficult to find accurate corresponding points in inherently ill-posed regions such as occlusion areas, repeated patterns, textureless regions, and reflective surfaces."

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