| ▲ | Geolocating a random island using geometry and CUDA programming(yassa9.github.io) |
| 158 points by yassa9 3 hours ago | 39 comments |
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| ▲ | NKosmatos 2 hours ago | parent | next [-] |
| Excellent write up and an enjoyable read! Reminds me of the “good old times” where posts on HN were written by humans and with a specific writing style like yours.
You could’ve used a little bit more of geoguessing to narrow down results, or do a brute force visual check on the last hundred or so ;-) |
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| ▲ | jambalaya8 a minute ago | parent | next [-] | | agree! AWESOME work! | |
| ▲ | yassa9 an hour ago | parent | prev [-] | | yea, thanks :D , I used a tiny idea from geoguessing, that I banded the search on islands only in latitude between -30 to +30 deg. based on the sky and the tropical vibes in the img , and it worked ! |
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| ▲ | bmurray7jhu 2 hours ago | parent | prev | next [-] |
| For drones and missiles, this technique is known as Terrain Contour Matching. If terrain contour are measured optically, navigation is independent of RF jamming, unlike GNSS. https://en.wikipedia.org/wiki/TERCOM |
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| ▲ | yassa9 2 hours ago | parent [-] | | oh, wow,
I didnt know that existed, thank u, sure gonna look into it |
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| ▲ | o4c an hour ago | parent | prev | next [-] |
| Really great article! OP, you did an awesome job breaking down a complex problem into manageable chunks and synthesizing the solution. |
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| ▲ | dwa3592 42 minutes ago | parent | prev | next [-] |
| This is awesome. I worked on something similar a few months ago. It is a general purpose navigation system based on TERCOM and dead reckoning - https://github.com/deepanwadhwa/anumaan |
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| ▲ | num42 14 minutes ago | parent | prev | next [-] |
| Good article! Off-topic, Is Palantir doing the same thing with its internal software to geolocate? |
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| ▲ | yassa9 9 minutes ago | parent [-] | | thanks ! no idea about Palantir, but in my opinion, this can not be automated , needs much manual work and tons of trial and error |
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| ▲ | ImJasonH 40 minutes ago | parent | prev | next [-] |
| Excellent read, I loved it. Incidentally, the image seems to be the one the resort uses on their website! https://oanresort.wixsite.com/chuuk |
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| ▲ | yassa9 25 minutes ago | parent [-] | | thanks, and yea, it should be solved easily by passing the img to google lens, the website is the first result, but I found a fun opportunity to solve it in different way |
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| ▲ | lexlambda 2 hours ago | parent | prev | next [-] |
| OpenStreetMap data really is a godsend for such OSINT purposes.
Works much better in populated areas too, with more features like roads, shops, electric lines that can be used to search. |
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| ▲ | GaryNumanVevo an hour ago | parent | next [-] | | Claude / Gemini + OSM Turbo is a crazy you can do natural language queries like "find me a bus stop in germany that's surrounded by more than 5 three story buildings" | |
| ▲ | yassa9 2 hours ago | parent | prev [-] | | yea , heard about them before, but didnt know that whole treasure till I really used it , impressive |
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| ▲ | cecinuga 3 hours ago | parent | prev | next [-] |
| I read all the process, literally awesome, i don't do OSINT (i know only what is this) and i think that's very cool |
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| ▲ | yassa9 3 hours ago | parent [-] | | thaaank you !!
Its my first ever challenge to do, and yea, I really found my passion |
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| ▲ | ape4 an hour ago | parent | prev | next [-] |
| What about tides? Would the outline of the island be different based on the time of day. |
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| ▲ | bitcurious 2 hours ago | parent | prev | next [-] |
| It’s interesting that most top contenders don’t pass the eyeball halo check, seems like there’s room to optimize that filter in code. |
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| ▲ | yassa9 2 hours ago | parent [-] | | yea, good observation, my guess is its the data more than the filter. OSM coastline polygons are generalized to different degrees depending on who traced them and from what imagery, so the fine shape detail a halo check would key on often is not in the geometry at all. I observed that at the end, didnt push on it further though. It already passed and I was super exhausted |
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| ▲ | phalanxx 2 hours ago | parent | prev | next [-] |
| What do you mean by no LLM generation if an LLM did all the coding based on reading through the .py files? Pangram isn't kind to "your" text either. |
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| ▲ | yassa9 an hour ago | parent | next [-] | | I meant the blog itself, the writeup, the steps and the walkthrough all by hand
, the final code u see is llm refined, of course, I wont publish my messy and spaghetti files with much tests, failures and dead ends, also vizualizations functions to produce that green maps , and faulty versions of them but you are right, I should add that | | |
| ▲ | StilesCrisis an hour ago | parent [-] | | Just by reading your actual messages it's easy to see that you didn't write the blog post entirely by hand. | | |
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| ▲ | StilesCrisis an hour ago | parent | prev [-] | | "No EXIF, no GPS, no camera make or model." Yeah, a human definitely wrote this. Nothing fishy here. (Why would the camera make or model matter???) | | |
| ▲ | yassa9 an hour ago | parent | next [-] | | ok, if u came with the whole conclusion by only this line, ok
, but to answer u, ( I hate to justify myself , but have to )
I started writing the blog after I started solving another challenge from gralhix : https://gralhix.com/list-of-osint-exercises/osint-exercise-0... and the part of the solution came from the metadata, the camera model, you can check urself, so when I came back to write the blog, it just came by flow, | |
| ▲ | voidUpdate an hour ago | parent | prev [-] | | If you know the camera make and model, you might be able to get lens parameters and get better estimates of real world geometry from the image | | |
| ▲ | yassa9 an hour ago | parent [-] | | yea thank u, that's another part, but mainly it would hard although knowing that, because you need to know elevation of the drone or the camera, which is also extremely difficult (I already mentioned that in the blog) | | |
| ▲ | StilesCrisis 37 minutes ago | parent [-] | | The camera make and model wouldn't tell you the lens parameters. The EXIF would, but that was already covered in the triplet. |
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| ▲ | hhh 2 hours ago | parent | prev | next [-] |
| great blog and great writeup |
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| ▲ | piterrro 2 hours ago | parent | prev | next [-] |
| really impressive, could that be the way to locate yourself without GPS? assuming we know more/less where we are |
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| ▲ | yassa9 2 hours ago | parent [-] | | yea, search about geoguessing on youtube, people like Rainbolt,
https://www.youtube.com/@georainbolt they literally memorize and get patterns of every possible road, place, map of any area (scanned by google earth), getting exact coordinates from single image, and play competitions and world cup based on that they do really nice videos about finding places in old photos people ask for |
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| ▲ | grodes 2 hours ago | parent | prev | next [-] |
| impressive |
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| ▲ | fenestella 2 hours ago | parent | prev | next [-] |
| [dead] |
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| ▲ | ohyoutravel 2 hours ago | parent | prev | next [-] |
| > NOTE: this is a genuine human work, didnt use LLM generation. A million upvotes from me. |
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| ▲ | yassa9 2 hours ago | parent [-] | | haha, thanks :D
I was hesitant to whether write it or not,
but I really really despise llm generated posts and blogs
and im glad someone appreciated it |
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| ▲ | hno8a34nwn an hour ago | parent | prev [-] |
| This is the real takeaway |