The angle at which he's looking towards the mirror starts changing. He sees things that weren't previously visible, and not just small details, entire people, rooms even. He manages to somehow locate Zora within the photo. It wasn't like Deckard simply zoomed in on her reflection within the mirror, he was definitely rotating his view.
My question is, is this technology ever explained?
Any theories/insight would be appreciated!
What Deckard is doing might be possible. He is forensically analyzing the photo he found, but how is he doing it?
Two ideas I can think of are:
Scenario 1) (more likely) In the future, all cameras have additional light sources (quick laser pulses firing) to illuminate most areas hidden within the scene, and perhaps a plenoptic camera. This additional data (of objects hidden from view) is embedded in the traditional picture as metadata. So Deckard can now navigate through this scene and render the additional data on the hidden objects using the computer.
Scenario 2) (less likely) In lieu of having additional light sources and/or plenoptic lenses, one can use machine learning.
In pretty much all photos, there is more data than just a pretty picture. There are light sources from the environment (and traditional flashes from the camera). Perhaps one can infer the approximate location, intensity, and nature of the light sources, say, based upon the shadows and flaring in the picture. From there, one can trace the light rays around the room to see what objects, not present in the picture, actually influence the resulting light intensity in the picture. From there, one can work backwards to make an educated guess as to the shapes and optical properties of those hidden objects. Perhaps this can be accomplished by some artificial intelligence running on a crazy fast computer.
In the 2) scenario, one can assume the Esper machine employs machine learning/ray tracing/etc. to infer what the missing data is in the photograph, as it's based upon the existing light field already in the picture. The computer AI fills in this missing or blurry parts of the photo, approximating data in real time, as Deckard navigates through the scene.
Of course, the deeper he dives into the picture, the more approximate and uncertain the hidden objects will be due to the sheer amount of assumptions and computation needed.
Lo and behold, in either case, Deckard actually finds some actionable evidence from data hidden to the human mind, but present in the picture.