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Here's an anecdote. My friend's apartment got burglarized many years ago and when we looked at the security footage we clearly saw the thieves taking everything

Here's an anecdote. My friend's apartment got burglarized many years ago and when we looked at the security footage we clearly saw the thieves taking everything, their faces were impossible to recognize though, due to low resolution. Ever since that happened I kept thinking of a video codec that would store the whole video in low-res but recognize faces and encode those parts in ultra high-res. I hope research like this can lead to better security. OTOH, government surveillance...

daenz 7y ago
OpenCV has a module called "super resolution"[0] whose goal is to reconstruct high-quality images from multiple low quality images. 0. https://www.youtube.com/watch?v=E6mePD21sIU https://www.youtube.com/watch?v=E6mePD21sIU
- CamperBob2 7y ago
  That's terrible. I want my 1:35 back
  - jonplackett 7y ago
    Try this instead. Best example of enhancing on the internet. https://www.dailymotion.com/video/x2qlmuy https://www.dailymotion.com/video/x2qlmuy
- taneq 7y ago
  Don't they do something like that to boost the resolution of space telescopes? Also I seem to remember reading something about processing a stream of images from an earthbound telescope to cancel out atmospheric distortion.
  - AlanYx 7y ago
    Space telescopes don't do super-resolution of the type used for video, but they do something a little similar. They use a technique called aperture synthesis which combines signals from a collection of instruments so that they have the same angular resolution as a much larger virtual instrument.
- marsokod 7y ago
  Super resolution can only do so much. Basically, a x2 or x4 improvement at best, especially on features more complex than text. Also, as soon as you compress your video stream you lose a lot of information that would actually be used by these algorithms. If a high res stream is available, it is much better to use it. A basic face detection algorithm and snapshots of them saved regularly would go a long way and are really simple to implement.
nrp 7y ago
Many video conferencing/calling applications already do this, allocating more bits to regions recognized as faces when encoding. You can test it out in FaceTime for example by showing your face vs obscuring enough of it that face detection fails.

daenz 7y ago

OpenCV has a module called "super resolution"[0] whose goal is to reconstruct high-quality images from multiple low quality images. 0. https://www.youtube.com/watch?v=E6mePD21sIU https://www.youtube.com/watch?v=E6mePD21sIU

CamperBob2 7y ago
That's terrible. I want my 1:35 back
- jonplackett 7y ago
  Try this instead. Best example of enhancing on the internet. https://www.dailymotion.com/video/x2qlmuy https://www.dailymotion.com/video/x2qlmuy
taneq 7y ago
Don't they do something like that to boost the resolution of space telescopes? Also I seem to remember reading something about processing a stream of images from an earthbound telescope to cancel out atmospheric distortion.
- AlanYx 7y ago
  Space telescopes don't do super-resolution of the type used for video, but they do something a little similar. They use a technique called aperture synthesis which combines signals from a collection of instruments so that they have the same angular resolution as a much larger virtual instrument.
marsokod 7y ago
Super resolution can only do so much. Basically, a x2 or x4 improvement at best, especially on features more complex than text. Also, as soon as you compress your video stream you lose a lot of information that would actually be used by these algorithms. If a high res stream is available, it is much better to use it. A basic face detection algorithm and snapshots of them saved regularly would go a long way and are really simple to implement.

nrp 7y ago

Many video conferencing/calling applications already do this, allocating more bits to regions recognized as faces when encoding. You can test it out in FaceTime for example by showing your face vs obscuring enough of it that face detection fails.