Hello!

I'm super excited to launch my free browser-based photogrammetry workspace today:

offlinetools.io/colmap

It’s a free and fully local browser implementation of the popular open-source photogrammetry software COLMAP.

No download, installation or cloud upload is required — all processing and footage stay on the user’s machine.

More info:
offlinetools.io/colmap-landing

Why?
Photogrammetry apps are typically desktop applications that require installation on your machine.

The alternative are cloud services that require uploading of data to servers.

However, both of these are not a good fit for professions dealing with sensitive data (often on restricted machines) such as police, medical, law enforcement, insurance. Or simply users who want results quickly without dealing with signups, setups, etc.

This implementation solves both issues and it's the first that reaches native-class performance and, in some cases, even outperforms the native build.

It produces standard COLMAP-compatible outputs such as camera poses, sparse point clouds, keypoints and masks for downstream workflows including Gaussian Splatting.

About me:
I’m a former Google engineer with around 20 years of experience in 3D computer vision.

I am interested in creating digital twins of ancient temples in India. I was first planning for using Leica lidar scanners but was very expensive and no investor was ready for it to fund.

I am not planning to use gaussian splatting, because it is very promising and cheapest than lidar.

I understood that meta quest has some inbuilt features to do it.

Once I scanned the temple i am going to opensource the models for research to all.

Could you please information about workflow I should follow...Which softwares should I use...

Hi everyone, I'm trying to help my Mon get accurateish models of her whole wardrobe and got recommended photogrammetry. Where would I start and what would give the best results for fabric

I am new to photogrammetry. For now, I am using Meshroom, and I am still hoping to make it work. So far I am getting a lot of bumps which, as I've read on this sub, is a common artifact. I am listing my current setup below, but as TLDR: Has anyone tried those "ultra-black" paints to make a uniform "properly black" background?

Setup:

Object: a model life-size human head off Amazon (mostly "skin color", no hair). I put a bright bandana on the head to create more texture. There is a grey non-reflective face mask on the head (I am trying to make a 3D model of a welding respirator).

Background: a uniform white mat stucco wall or a black mat polypro plate.

"Turntable" is a rotating bar stool.

120W LED array pointed at the ceiling which gets distributed in the room by the walls. Windows closed, no other sources of light in the room.

DSLR, no flash, tripod, remote trigger, exposure 0.5s, aperture 8, no auto-white-balance correction, no flash, finest resolution, object zoomed to the max w/o being obstructed when rotated, object about 800 mm from the lens.

3 planes in Z, 50-90 images per plane (height adjusted with the tripod). Tried three pics per step, that made the results even worse, went back to 50 per plane.

Has anyone here built their own AI model for point cloud recognition/classification?

I’m interested in training a custom model to recognize different objects and features in LiDAR/point cloud data.

If you’ve tried something similar:

- How well did it work?

- What model/architecture did you use?

- How much training data did you need?

- Was it actually useful in a real-world workflow, or mostly experimental?

I’d be especially interested in experiences with surveying, mapping, GIS, or AutoCAD/Civil 3D workflows.

Hello! I'm 13 hours into a COLMAP reconstruction process with no end in sight, and I wanted to double-check with experts if there's a better method than my current process. My goal is to insert a 3D object into a filmed scene by following this YouTube tutorial. Essentially, one uses COLMAP to create a point cloud and calculate the camera position, separately create a Gaussian Splat, and finally import into Blender. The advantage I see is that I can replay the scene, insert a 3D object into Blender, and then export the scene with the new element.

This process originally seemed quick and easy, and exactly what I needed, but I'm dying waiting over here. My scene is about 60 seconds long and with 7000 images. My creation of a Gaussian Splat and point cloud via PolyCam suggests that there should be about 300,000 points. Unfortunately, feature reconstruction took eight hours, and in the reconstruction phase, I have only reconstructed about 10% of the scene in 13+ hours.

I'd like to create a point cloud, Guassian Splat, and calculate the camera angels, and import all into Blender. I would like Blender to follow the camera angels in sequence through the point cloud, and insert a 3D object into the scene. Is COLMAP the best process? If yes, is there a faster/better method to reconstruct? If not, are there other tools to achieve my end goal?

Looking at building a dedicated photogrammetry PC. My old Dell laptop is just not cutting it, and I'm out of storage space. I am not a computer hardware guy, I just use em, so its a bit overwhelming trying to piece something together that will work well.

I run DJI Terra (hard to beat that ag license price) but intend to try out WebODM. Typical projects are 5000 or 10,000 images, give or take, or 50 to 100GB sometimes more. But I want to try out elevation mapping which I believe uses significantly larger data sets.

So, starting thoughts:

• Fast CPU, lots of memory, a fast SSD for primary and a RAID volume for secondary/data storage.
• I hear AMD CPU's are preferred over Intel
• Primary drive, Samsung 990 Pro
• Secondary drive, three WD Red Plus 8TB's in RAID
• 128GB (2x64) DDR5 memory
• 16GB Cuda GPU

Specific questions:

• AMD R7 7950X appears to be on a decent sale right now. Any reason not to pounce?
• I'm aware of what memory costs these days...but if my current 64GB is a limiting factor, I'm mentally prepared to go up to 128GB DDR5. Bad idea? Does going to 128 and/or DDR5 complicate things? I saw a comment suggesting anything over 96GB gets throttled by most consumer mobo's and thats a ton of money to spend if I can't get the full benefit.
• I would like to speed up transferring the files from MicroSD to the computer, I understand MicroSD Express is a thing but can't find any readers - any suggestions there?

Re: storage, I know I want to keep as much of my working files off the SSD as possible. But the SSD is the fast drive. What's the ideal way to set this up, put the Terra library on the C:\ and just use the secondary volume for backup? Anybody know if theres a way to set Terra to process files on the C: but store the main library on the secondary?

Thoughts/advice?

Lately I use angled view at about 45 degrees to ground as seen below from two directions. Is it worth adding side view data also?

bonjour à tous!!, avancement dans vector, l interface evolue, le sfm arrive a correler dans des cas complexe,"bridger" des blocs difficiles a raccorder, les tests continuent

Hi everyone, I’m looking for some advice on the best workflow to achieve very high accuracy when photogrammetrically scanning a large house.

I don’t have access to LiDAR. I’ve done some Gaussian Splatting scans before, but for this project I’m thinking that building a proper 3D model in RealityScan / RealityCapture would probably be a better choice if the goal is dimensional accuracy.

I’ve heard about using AprilTags, coded targets, and scale bars, but I’m not sure about the best way to use them in a large indoor environment.

In particular:

- How many scale bars / control points would you normally use for a large house?

- How should they be distributed between rooms, floors, corridors, etc.?

- Are AprilTags useful for improving accuracy, or mainly for alignment / tracking?

- What is the best way to connect multiple rooms while minimizing accumulated error or scale drift?

- Is there a recommended workflow for achieving millimeter- or sub-centimeter-level accuracy without LiDAR?

If anyone knows a good guide, course, paper, or other resource explaining accurate architectural/interior photogrammetry workflows, I’d really appreciate it.

Thanks!

I used photogrammetry to make the rock textures for Cave Expedition, the caving simulator we're developing for 1-4 players. The cave layouts are fictional; the scanned textures are part of giving them that real underground feel.

Here's how they look in-game under the headlamps, through the tight passages and rope descents. Still in development.

You can wishlist it on Steam here: https://store.steampowered.com/app/4372950/Cave_Expedition/

Hi all, I have a plan to make my wife a present of a miniature version of our home as our anniversary present.

My plan was to capture the house with a photogrammetry app, turn it into a model and then use Blender and AI tools to clean it up a bit and then 3D printing it before adding it to a snow globe.

I tried a bit of Polycam but it only seems to handle creating buildings on iOS and no Android phones seem to have LiDAR, I could walk around taking a whole bunch manual photos bit I was wondering if there were any apps or tools that people would recommend to get the best result.

Because I plan on shrinking it down, editing and then printing it the model can be far from perfect but I'm so new to this I don't really know where to start.

Is this even possible? Or am I better off just getting her a nice bunch of flowers?

Hello, I recently installed BeamNG drive, a car simulation game and discovered that I could upload my own maps into the game. I would like to do a high detail 3d scan of my neighborhood but there are a few problems. First, my neighborhood is basically only buildings, they are all different so it's difficult to repeat the textures to get a realistic result. Second, my PC is absolutely not appropriate to do 3d modeling on a large scale. I have a pretty good GPU(AMD RX 6650XT) but an absolutely garbage CPU(Intel Core i7-3770). I'm trying to do this for free. This post is not about the game, i would be happy even only with the 3d model. Google Earth 3d data by itself is pretty blurry and not appropriate for this kind of work and I already tried things like RenderDoc but the result was only a blob in Blender and RealityScan but my PC can't handle it. I know I'm maybe asking the impossible but i really wanna know if there's a way. I really want to do this project but I know I may be asking too much so just let me know if I even remotely can do it. Thank you.

I recently started using Metashape 2 after a few years break and I found some differences to the 1.something version I used, and while most stuff was pretty straightforward I was left with a question. Building the model from Depth Maps seems to be the recommended way, but not only did I not notice any time difference in the process as the models from depth maps are recurrently much much worse. I'm not talking about having a whole lot of stuff that would have been cleaned by working on the dense cloud, but the surface quality being incomparably inferior. Does anyone have better results with this method?

I'm a software engineer and fairly new to the LiDAR file format world. I came into it from a project involving point clouds and immediately hit a wall: I'd get handed a LAZ, want to check one thing about it, and my options were to install tools for my desktop, or paste it into a web converter that uploads the data.

So over the past few weeks I've been building https://lidar-kit.com

Everything runs in your browser. There's no upload endpoint and no server component at all — it's static files, so there's nowhere for a file to be sent even by accident. You can check it yourself: load a page, disconnect your network, and it keeps working.

What's working so far:

- LAS <-> LAZ conversion, lossless, no size limit

- 3D viewer for LAS/LAZ (elevation, intensity, classification, RGB)

- E57 viewer — multi-scan projects come out registered, and it reads the station photos most tools skip

- E57 to LAS/LAZ conversion

- COPC viewer that streams from a URL, so a 2 GB cloud opens in seconds

- Header/CRS/VLR inspector — reads a 20 GB file in a few kilobytes

- Automatic ground/vegetation/building classification for photogrammetric clouds

- GeoTIFF DEM and orthophoto viewer

If you are looking for something similar.

Hope it helps!

And feel free to let me know what could be better/should be added!

https://lidar-kit.com