ConsistentlyInconsistent

@x_acaicia If you send it to me I would love to see it, I'm not far off finishing my q&a video.

@ConsistInconsis Howdy! I've been working on my own sparse voxel engine. Currently, I'm able to locate sub pixel objects moving >5m/s @ 152m away using 3 cameras at an average of 26ms per voxel engine frame from noisy images with moving objects, like clouds and trees.

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.

@oscilllator download more ram

@ConsistInconsis You didn't answer the question of how you will tackle the memory usage. Any voxel grid big enough to both project single pixels into and track over a usable volume will be many TB in size.

Apologies for the double repost, I wasn't expecting either of the first two posts to pop off like they did so I made this one so that the explanation is as tight as possible which seems to have cleared up the confusion.

This is a video demonstrating a brand new asteroid tracking technique I made that is so powerful that it can precisely track Stealth Fighters better than any other Stealth tracking technique in existence even when it is using just three $30 webcams. This same technique can be used interchangeably with thermal cameras and can majorly upgrade Radar systems. It is also able to massively increase the effective resolution of 3D scanning techniques such as CT scanners and cryo electron-microscopy. I've added notes at 4:15 and at 9:10 which go into detail about why I think this hasn't been done yet and what the things are that you think that this is but it isn't. Pretty much all of the problems you can think of with the system are extremely easy to fix if you use a little bit of brainpower to solve them.

Yeah, sorry about that, I was hoping it wouldn't show up on people who have already seen the last two vid's time lines. It was just irking me that I explained some of the things in the video poorly and that there may be people who could use this. Comment section seems to be calm now.

@ConsistInconsis This is turning into spam. If you really think you've done something so novel in only a few hundred lines of code with only basic ray casting and matrix math then why don't you write a paper and publish it? x.com/Lon/status/195…

@KO_Sulli arguably you could, yes.

@ConsistInconsis Can this be applied to early forest fire warning systems?

@MichaelAlleged @elonmusk fuck, they might have Darth Vader on their side as well

Who said you would? This is air defense 101 first of all, emit and die, the F-35’s radar is made for this second of all, onboard sensors are not the only thing you have to worry about when fighting stealth aircraft. Every nation fielding them is backed up by absolutely insane spy satellite capabilities, which in a theatre, will constantly be searching high and low for you and you will likely end up struck long before the strike packages come within range. This is the entire point of stealth aircraft and why every nation worth its military salt is pursuing them in numbers.

Proving that @elonmusk 's theory that Stealth Fighters can be tracked with cheap cameras is correct by using a brand new technique that I made to detect asteroids by precisely tracking planes better than any current radar with just three $30 web cams.

@MichaelAlleged @elonmusk Why would I permanently keep my radar on instead of waiting until the aircraft has entered my approximate range and then using it?

@ConsistInconsis @elonmusk > to better understand the difficulties in seeing stealth fighters I understand them better than you do, considering I worked on both them and SAMs for shooting them down. Also if you think range has nothing to do with it, you’re far behind the guy who invented throwing rocks.

Also it really doesn't take that much brain power to solve any problems with using this. In reality you would probably use 4 or 5 zoomed thermal cameras that pan across the sky in sync with each other. I'm just demoing the power with webcams. And it also works to improve Radar.

In reference to this tweet:

A fan of the video posted a clip of him using the technique to precisely track planes at Shanghai's international airport in real time using three 30 dollar web cameras. Imagine what you could do if you used more expensive infra-red cameras instead👀.

@spacesudoer @elonmusk lmao

@ConsistInconsis @elonmusk Do you realize this video exactly proves what Elon said in that post? You look like a complete retard here 😂😂

Dunking on @elonmusk by actually precisely tracking Stealth Fighters with cheap webcams using a technique I made for detecting asteroids.

@spacesudoer @elonmusk

And best of all, you can use this to majorly boost the effectiveness of radar, even if optical and thermal systems aren't working due to cloud cover.

Also it really doesn't take that much brain power to solve any problems with using this. In reality you would probably use 4 or 5 zoomed thermal cameras that pan across the sky in sync with each other. I'm just demoing the power with webcams.

@spacesudoer @elonmusk youtube.com/watch?v=cwq6wL… and did he actually build it?