Geolocating a random island using geometry and CUDA programming

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yyassa9 about 3 hours ago 35 commentsRead Article on yassa9.github.io

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Discussion (35 Comments)Read Original on HackerNews

num42•1 minute ago

Good article! Off-topic, Is Palantir doing the same thing with its internal software to geolocate?

NKosmatos•about 1 hour ago

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 ;-)

yassa9•about 1 hour ago

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 !

bmurray7jhu•about 2 hours ago

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

yassa9•about 2 hours ago

oh, wow, I didnt know that existed, thank u, sure gonna look into it

o4c•about 1 hour ago

Really great article! OP, you did an awesome job breaking down a complex problem into manageable chunks and synthesizing the solution.

yassa9•36 minutes ago

thanks, appreciate it

dwa3592•29 minutes ago

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

ImJasonH•27 minutes ago

Excellent read, I loved it.

Incidentally, the image seems to be the one the resort uses on their website! https://oanresort.wixsite.com/chuuk

yassa9•12 minutes ago

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

lexlambda•about 2 hours ago

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.

GaryNumanVevo•32 minutes ago

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•about 2 hours ago

yea , heard about them before, but didnt know that whole treasure till I really used it , impressive

cecinuga•about 2 hours ago

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

yassa9•about 2 hours ago

thaaank you !! Its my first ever challenge to do, and yea, I really found my passion

ape4•about 1 hour ago

What about tides? Would the outline of the island be different based on the time of day.

yassa9•31 minutes ago

honestly, I didn't think about it, I just trusted the OSM polygons

bitcurious•about 2 hours ago

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.

yassa9•about 2 hours ago

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

phalanxx•about 1 hour ago

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.

yassa9•about 1 hour ago

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•about 1 hour ago

Just by reading your actual messages it's easy to see that you didn't write the blog post entirely by hand.

StilesCrisis•about 1 hour ago

"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•about 1 hour ago

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•about 1 hour ago

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•43 minutes ago

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)

hhh•about 2 hours ago

great blog and great writeup

yassa9•about 2 hours ago

thannks, really grateful :D

piterrro•about 2 hours ago

really impressive, could that be the way to locate yourself without GPS? assuming we know more/less where we are

yassa9•about 2 hours ago

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

hno8a34nwn•about 1 hour ago

This is the real takeaway

grodes•about 2 hours ago

impressive

ohyoutravel•about 2 hours ago

> NOTE: this is a genuine human work, didnt use LLM generation.

A million upvotes from me.

yassa9•about 2 hours ago

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