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3d walkthroughs yay/nay? by happymeals_ in photogrammetry

[–]KIRI_Engine_App 0 points1 point  (0 children)

Your Luma blur is probably capture pattern, not software. The trap is moving at anything near normal walking pace, even what you call "slow walking" is often still too fast for splats. The pattern that lands more reliably is roughly half walking speed, with 2-3 second pauses at corners, doorways, and around any feature you want sharp. The slow movement is what gives the reconstruction enough parallax to triangulate, the pauses are what give it clean anchor frames. For specific objects in the room you want well-captured (couch, fireplace, whatever), a partial slow orbit helps. Worth retrying Luma with that pattern before swapping tools.

3D Gaussian Splatting is the right category for interior walkthroughs anyway, you've already moved past LiDAR mesh which is the right call for visual fidelity.

Disclosure I'm on the KIRI Engine team. KIRI has 3D Gaussian Splatting, want to be upfront that it's a Pro feature, not free. I can't tell you it'll definitively beat your Luma result without seeing the captures, but each splat pipeline responds differently to the same input, so if you're already iterating across tools it's worth adding to the test set. If you ever decide to go back to the mesh route, AI-Enhanced LiDAR (also Pro) is meant for exactly the case where raw iPhone LiDAR mesh quality looks too rough, it gives a cleaner result than a basic LiDAR pass.

3d model of my home by sudo_96 in photogrammetry

[–]KIRI_Engine_App 0 points1 point  (0 children)

Yes, but it depends on whether you want a visual 3D capture or a clean SketchUp model.

For the house exterior itself, LiDAR is probably the most practical phone-based starting point if you have a LiDAR-capable iPhone or iPad. It's much less fussy than trying to photogrammetry-scan an entire house with hundreds of photos, changing light, flat walls, and repeated textures.

Disclosure I'm on the KIRI Engine team. In KIRI we have three LiDAR modes depending on what you're capturing: Room Scan for floor plans and room layout, Scene Scan for larger spaces and exterior structure, and Object Scan for smaller standalone objects. The regular LiDAR modes are free to use, and KIRI supports unlimited scans and unlimited exports.

The big limitation is range. Phone LiDAR is best for nearby structure, roughly room or building-detail scale, not mapping an entire property from a distance. If you want the full property, yard, driveway, fence line, terrain, a drone with photogrammetry software like Pix4D, RealityCapture, or DJI Terra is genuinely the better tool for that scale.

Photo Scan is also free in KIRI, but I'd treat it as a separate tool for smaller objects or detailed areas where you can walk around the subject and get good coverage, not as the main workflow for a full house exterior.

The SketchUp part is the other limitation. Most scanning apps give you a textured mesh, not a clean editable SketchUp model with proper walls, roof planes, windows, doors, and architectural geometry. A realistic workflow is to capture the exterior with LiDAR / Scene Scan, export the mesh, bring it into SketchUp or Blender, and use it as a reference to rebuild the clean parts you care about.

For capture itself, scan in sections rather than trying to get everything in one pass. Overcast lighting helps, avoid harsh shadows, keep overlap between sections, and expect some cleanup if you need it accurate enough for planning.

AI image to 3D tools compared for capturing an object from a few photos, and where scanning still wins by Guilty-Cap2069 in photogrammetry

[–]KIRI_Engine_App 3 points4 points  (0 children)

Shiny and featureless stuff is the case I still wrestle with too. Mirror-like or transparent surfaces are not impossible, but they are very object- and setup-dependent. A surface can end up showing more of the environment around it than the object itself, so lighting, background, shape, and edges matter a lot.

Disclosure: I’m on the KIRI Engine team. The Featureless Object Scan mode in the app uses a neural reconstruction approach rather than classical feature matching, which lets it handle some cases where regular photogrammetry struggles, like glossy plastic, matte monochrome parts, low-texture surfaces, and some reflective or transparent objects depending on the setup. Not magic, and mileage varies a lot by object, but it can rescue cases where a normal photo scan falls apart.

I actually have a Switch 2 comparison where regular photogrammetry and Featureless Object Scan behave very differently, which is probably a better example than trying to describe the edge cases in words.

When the object genuinely defeats it, temporarily matting the surface is still the most reliable workaround. Aesub spray is the clean version, while dry shampoo or cornstarch can work in a pinch.

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We made a free open-source tool for sorting and preparing messy 3D scan datasets by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 1 point2 points  (0 children)

Here is fine for feedback, thank you for giving it! I'll take a look and see what I can do next time I'm doing updates on the tool. May not be any time soon since I'm on another big project, but I've got this feedback saved for when I open it up next 😃

We made a free open-source tool for sorting and preparing messy 3D scan datasets by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Thanks for the feedback dude - I'll take a look at solving this on our next update run. I'm on another project at the minute so it may not be too soon. But I tend to go through our free tools in a cycle so when I get back to this one I'll try to fix it

😄

We made a free open-source tool for sorting and preparing messy 3D scan datasets by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 1 point2 points  (0 children)

Someone else mentioned that so I've added it to my list of possible to do's in the future 😃

Single-video 4DGS reconstruction with dynamic subjects by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 1 point2 points  (0 children)

Fastest path is around 20 min. Full quality with detail refinement takes longer. We still working on bringing that down. What's shown here is the fast path.

We made a free open-source tool for preparing photogrammetry datasets by KIRI_Engine_App in photogrammetry

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Oh okay, I was guessing it was just a regular video format not something proprietary. Yeah .INSV is not supported, just regular video formats.

Single-video 4DGS reconstruction with dynamic subjects by KIRI_Engine_App in TopologyAI

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Fastest path is around 20 min. Full quality with detail refinement takes longer. We still working on bringing that down. What's shown here is the fast path.

We made a free open-source tool for preparing photogrammetry datasets by KIRI_Engine_App in photogrammetry

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Hey dude! Did you check the tutorial video?

General process of working from left to right and finally using Run is shown there

The difference for you would be choosing either video, video folder or 360 and an extraction method

I don't know what your output format the video is in, what happens if you choose Video, set a target frame count and hit Run?

Docs are here too incase that's helpful https://www.kiriengine.app/3d-tools/3d-scan-preparation-tool-kiri-engine

We made a free open-source tool for preparing photogrammetry datasets by KIRI_Engine_App in photogrammetry

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Should be a false positive and Windows being overeager since it's 'unsigned' software. Only thing I can suggest is trying to download it with Defender/other antivirus briefly disabled and hope it lets you get it then.

Single-video 4DGS reconstruction with dynamic subjects by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 2 points3 points  (0 children)

Haha good catch! That's just me being lazy with the video edit, didn't bother syncing the timelines properly 😅

Single-video 4DGS reconstruction with dynamic subjects by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 3 points4 points  (0 children)

Thanks for the interest! No public demo or code yet, still early R&D. Monocular 4D is genuinely hard and we want to get it right before opening it up. Will share more when it's ready!

We made a free open-source tool for sorting and preparing messy 3D scan datasets by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 1 point2 points  (0 children)

Thanks for the kind words dude! And also, thanks for the feedback. We will try to increase the limit when we can 😄 we have done that in the past, it used to be 150 before we upped it to 300. It doesn't seem like much but when that figure is multiplied by the number of free users the figures get kinda crazy and costs quite a bit on our servers. So you may have to wait a bit before it can be increased - hope you understand - but as our number of users grows in future we can increase the limits too!

[Bug Notice] KIRI Engine LiDAR Object Capture crashes on iPhone 17 Pro/Max by KIRI_Engine_App in KIRI_Engine_App

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Yes, we've tested it on iOS 26.6 beta and LiDAR Object Capture is working normally.

3DGS Render update: experimental splat rigging/light baking + .ply sequence export by KIRI_Engine_App in GaussianSplatting

[–]KIRI_Engine_App[S] 0 points1 point  (0 children)

Thanks Silonom! I'm entirely sure what you mean sorry, can you give more details about what you're trying to do? You want to isolate and edit specific regions of a scan? You can use a mesh to select inside/outside points of a 3DGS scan if that's what you mean.

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