Heat-assisted detection and ranging
nature.com
nature.com
https://github.com/FanglinBao/HADAR
and videos
https://purdue0-my.sharepoint.com/personal/baof_purdue_edu/_...
Most optical cameras work with reflected light, not direct emission. The source of light is usually away and at an angle; this allows for shadows, textures, etc.
I don't see why an IR camera can't work the same way as an optical camera, if reflected IR is used; IR photos under e.g. sunlight look fine enough.
Radars or lidars work with their own scanning sources of illumination: microwave, IR, or optical. I wonder if the HADAR uses its own source of IR; if it does, how different it from a LIDAR?
(All these mysteries can be solved for $29, but I'm not yet curious enough.)
- They use and combine both optical and LWIR data.
- They are able to split the IR signal into emissive and reflected, and thus measure the temperature and extract small variations (texture).
- They can get higher-res images using LWIR, and thus do (more) precise ranging using a stereo pair.
- Using the spectral information + some ML models, they are able to identify materials, and paint / augment pictures using this information.
That's actually impressive.
The thermal images in their examples seem to be intentionally using a wide temperature gamut to reduce the contrast in the image (and make it look bad). Most thermal imaging solutions will automatically adjust and give you a much better result.
Regardless I can see lots of benefits of integrating the two as basically another color channel. There's a lot of information available.
The problem with doing stereoimaging with thermal radiation is that almost all objects are glowing due to radiation emission which blurs out the 3d texture of the object. The example they give is if you have a lighbulb with some texture, you can't see it when it's on(you might experiment with this in various 3d engines). This makes it difficult to do stereoimaging because everything is so blurry.
To do this they develop a way to deconvolute the temperature, emissivity, and light reflected by the object(they call this texture). They assume that the much of the reflected light comes from a couple objects in the scene with known properties such as the sky and ground which allows them to get an estimate of surface normal and do something like inverse ray tracing to estimate the light reflected by the object.
They also estimate the emissivity by comparing the spectra to a library of spectra for different materials. I think they use this as part a second step in their inverse ray tracing to work out reflected light and temperature of objects. Much of this is detailed in the supplementary information[0].
It's interesting because they have a passive sensor for depth which works at night, but also estimates what objects are made of. It may degrade when there are fires which may break some of the assumptions they make to estimate reflection or spills of IR absorbing substances. Gasoline, CO2, methane, and other gases can strongly absorb in the infrared spectrum. Which may interfere with temperature and material estimates.
[1] https://www.theguardian.com/us-news/2023/jun/23/self-driving...
Really, though?
Second: mass production, interchangeable parts, reliable steel, telegraph and other basic uses of electricity.
Third: computers and everything related to them.
Fourth: all the buzzwords and not much substantial at this time — though when the dust settles, I won't be surprised if at least a few currently popular things are still seen as relevant and not merely flash-in-the-pan cultural artefacts like the 18th Amendment, patent medicine, or Spiritualism.
It doesn't belong in academic work, no matter how impressive the authors think it may be.