[formula1]

I appreciate you probably put a lot of effort out but your post largely sums up to "They are wrong, I've done extra curricular research to prove it, I have no alternative"

While noble, I cant help but wanting to understand what alternatives you were leading yourself done. As an example, light can arguably simplified to intersecting cylinders and spheres that bounce off surfaces to create new 3d shapes. Each shape also would have an origin 2d shape based upon whats reflecting it. an "eye" reads shape intersections with self and also can filter those intersections in respect to origin shape. After each bounce, the new shape takes form as the bouncing lights color multiplied by the color of the bounced object In low light situations, subtle luminosity differences can be enhanced.

What I did was offer an example. Perhaps youll one day be successful but I got the impression you are some kind of renegade with a mission. While I can certainly relate to that, I view science and building the future quite far from renegade status. And in the mean time, you gave me a sob story with no algorithms/solutions except for "take real pictures and compare them". As a lazy programmer, walking outside and discoveringvthe world doesnt interest me too much.

[sillysaurus3]

We can come up with hundreds of simplified lighting models. Have you tried the one you mentioned? Does it correspond to photographs, video? That's the hard work, and it's why I listed none.

Here's something specific: What did you mean by "multiply"? You cannot "multiply" colors. Not unless you concede that your model has nothing whatsoever to do with physical reality. And at that point, why not use a photo of nature (or your eyes' perception of nature) as a baseline comparison?

From http://www.feynmanlectures.caltech.edu/I_35.html:

"The phenomenon of colors depends partly on the physical world. We discuss the colors of soap films and so on as being produced by interference. But also, of course, it depends on the eye, or what happens behind the eye, in the brain. Physics characterizes the light that enters the eye, but after that, our sensations are the result of photochemical-neural processes and psychological responses.

There are many interesting phenomena associated with vision which involve a mixture of physical phenomena and physiological processes, and the full appreciation of natural phenomena, as we see them, must go beyond physics in the usual sense. We make no apologies for making these excursions into other fields, because the separation of fields, as we have emphasized, is merely a human convenience, and an unnatural thing. Nature is not interested in our separations, and many of the interesting phenomena bridge the gaps between fields."

Walking outside and discovering how the world looks is exactly how to improve your techniques as a graphics programmer.

[tizzdogg]

I work in film vfx, and if you think we dont compare our rendered images to real photographs and video constantly, then you dont really know how modern graphics are produced. We shoot reference for everything, and use things like gonioreflectometers to sample real world BSDFs. Yes, lighting models are always necessarily simplified from the real world physics. But the thing is that 99% of the time that doesnt matter, because most common types of surfaces are able to be reproduced accurately enough to fool the majority of people. I would wager that most of the CG things you see these days on TV or in movies you have no idea was CG.. it's only the bad stuff (or obviously impossible) that stands out.

I actually am a bit confused what you are arguing here.. all of these problems you're mentioning have been well-understood by graphics researchers for the past couple decades.

[sillysaurus3]

The main point was that film isn't interested in exact photorealism. As you said, it doesn't matter, because the simplified models are good enough. Therefore it's unlikely that the film industry will be the first to produce a fully computer-generated video that will be indistinguishable from a camcorder capture.

The reason most of the CG you see in TV or movies looks very good is because they take place within real video. We're not looking at a completely CG scene -- it's mixed with video from the real world. And that's a perfectly valid technique, but my comment was talking about 100% CG.

A secondary point re: the film industry is that artists must necessarily retain control of the art pipeline in order to create scenes that advance the plot. That requires the art pipeline to be flexible. The more flexible your art pipeline, the more productive your studio is. Yet that flexibility is precisely opposite to realism. Obviously, the more realistic a purely CG scene looks, the less flexibility you get, otherwise it wouldn't appear real; hence the argument that the vfx industry won't be the ones to produce the elusive fully-CG fully-realistic video. (It doesn't make financial sense for them to do so, if nothing else.)

[tizzdogg]

Again, I would wager that you have seen many, many shots on TV and in movies which were fully, 100% CG already. You just didn't notice because they really were indistinguishable. We've definitely already crossed that boundary in many areas, and the main things which still stand out is just bad work.

[danielvf]

I've been diving to light, color, and color perception the last couple weeks as part of a fun work project. I've got a diffraction grating spectrometer on my desk that measures light in half nanometer wavelengths. From the papers that I've read, and the stuff I've messed with so far, it seems that human perception of colour - on average - is well studied, and has been since the 1930's. We know how light gets into the eye, and how much each wavelength of light will excite the average eye's individual color specific sensors.

Once the info leaves the receptors, now that's a another story...

[scott_s]

Perhaps a way of stating it is that you want to create computer programs which do the same image processing that our brains do. That, I think, is what you're getting at: we don't see "reality", we see images processed by our brain, from signals received by our eye, mixed with a bunch of learned and instinctual models already existing in our brain. Accurately modeling the signals entering our eye is not enough. We also need to perform - at least approximately - the some processing that our brain does.

[jsprogrammer]

Do a search for photorealistic ray tracers. Photorealism is inevitable as we are only projecting onto finite displays. Enough samples from an accurate enough model will result in bits that are indistinguishable from a live capture.

Light can be multiplied, in a way, through interference.

[formula1]

so you want to store an amplitude and wavelength along with your shapes instead of color? Go for it. You want to add in psychological factors? Sounds wasteful.

Your type of examples seems like uts more useful for machine learning. Collect enough samples, build enough models, run enough tests and youll get something accurate-ish.