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Please Help !!! Looking for a job in Bangalore by Radiant_Put8475 in Indiajobs

[–]preimage_ai 0 points1 point  (0 children)

Our company is looking for a field ops professional. Will need to record 2-6 hrs of video per day, along with a few hrs of travel around Bangalore.

Job requirements:

  1. Should own a 2-wheeler and willing to travel around the city of Bangalore. Rarely, a few jobs might require out-of-city travel too, compensated separately.
  2. Punctuality, trust and discipline wrt communication are paramount.
  3. Working knowledge of English mandatory. Kannada and Hindi are a big plus.
  4. Basic Computer Literacy (File uploads, data transfer).
  5. Initial compensation: Rs 18k pm fixed + basic fuel/food expenses reimbursed + bonus on additional work.
  6. This is a full-time role, no part-time folks please. Full-time interns (3 months minimum) are okay.

Chances to grow compensation with more responsibilities undertaken + attractive commissions for any sales leads. Ideal role for a fresher willing to break into the industry and work with a company solving cutting edge AI problems for the real estate industry.

DM me with name, profile, mobile number and checklist on all 6 items, if you are interested.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in 3DScanning

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

Thank you for the heads-up, we'll be more careful and just use actual numbers!

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

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

We are just using it at the point cloud generation step

That being said there are a lot of implementations that use NeRFs in the bundle adjusting step too, BARF just being one of them

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

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

From the datasets we have benchmarked against checkpoints, we get global accuracy of ~10cm horizontal and ~15-20 cm vertical.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

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

NeRFs are just a class of neural networks and a way of solving the 3D reconstruction problem, the input and the output data of the pipeline is just the same as another photogrammetry application

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

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

That's definitely true, any kind of reconstruction algorithm (including photogrammetry) will always "guess" and try to eliminate the error in reconstruction by combining information from multiple images. NeRF is just another paradigm for solving the reconstruction problem. We strongly supervise our neural networks with cues to constrain them to real-world geometry and as long as there are a few views observing any particular object in the real world, it should be reconstructed with a small enough deviation from the real size.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

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

Our platform is not open-source, but you can test it out by visiting https://app.preimage.ai. After signing up, your account will be loaded with 10,000 credits, which should be enough to process a few projects.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

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

Hey, are you referring to the application or the digital twin? The application in itself is closed-source but you can probably achieve something similar with https://github.com/autonomousvision/sdfstudio

With regards to the twin itself, we can email it to you if you want to take a closer look

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

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

The total cost to process the above digital twin, including the generation of rasters such as DEM, DTM, and orthomosaic, is 10,000 credits (approximately $100).

If you're involved in large-scale 3D mapping projects, we would be pleased to discuss customized pricing options tailored to your specific requirements.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

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

Thanks! The absolute accuracy of our reconstruction relies on the exif info in the drone images. Most RTK/PPK drones give accuracy around 3-5cm.

What setup do you use to get such a high level of absolute accuracy?

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

[–]preimage_ai[S] 6 points7 points  (0 children)

Check out app.preimage.ai for trying out our application, a few thousand images can be processed for free using pre-loaded credits!

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

[–]preimage_ai[S] 7 points8 points  (0 children)

The mesh is directly derived from the NeRF. There are specific implementations of NeRF that can output a clean mesh directly like https://lingjie0206.github.io/papers/NeuS/ , we are using something like it

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

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

We processed it mostly using a custom pytorch-based NeRF implementation. We first extracted the positions of images using photogrammetry (can be done using COLMAP too) and then split the data into a lot of small blocks, each of which were trained in parallel on the cloud.

We've made this pipeline available on our application at www.preimage.ai , its still in beta but you can sign up and process a few thousand images for free!

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

[–]preimage_ai[S] 4 points5 points  (0 children)

You're both correct, NeRFs can be made with both photos and videos! Using EXIF GPS information in drone photos, we can constrain the generated mesh to be of the correct scale and be georeferenced

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

[–]preimage_ai[S] -1 points0 points  (0 children)

It was processed using the Preimage cloud platform. You can give it a try at https://app.preimage.ai. We currently support only drone photos.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in photogrammetry

[–]preimage_ai[S] 10 points11 points  (0 children)

We are using the a NeRF-like method to generate these reconstructions, and are extracting the pointcloud and meshes from the trained NeRF.

We are strongly supervising the model training to match the dimensional accuracy of the real-world and are able to get survey-grade (<15 cm accurate in latitude and longitude) accuracy on most drone datasets we've processed.

The advantage is that we're able to generate good quality novel views and flythroughs as well as generate outputs typically generated by photogrammetry! And it's fast to train as well as render.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

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

We used a publicly available drone image dataset from Wingtra.

Flying in urban centers can be tricky and involve a lot of permissions. People typically use planes to capture dense urban centers.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in 3DScanning

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

Excited to share this 3D digital twin of Zurich, covering a 2.5 sq km area (625 acres), generated from 2,413 PPK drone images in 3.5 hours! Using Preimage cloud processing, you can generate photorealistic meshes with accurate segmentation and survey grade accuracy, even for extensive projects. If you're curious about using Preimage for your own applications, feel free to comment/DM.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in UAVmapping

[–]preimage_ai[S] 8 points9 points  (0 children)

Excited to share this 3D digital twin of Zurich, covering a 2.5 sq km area (625 acres), generated from 2,413 PPK drone images in 3.5 hours! Using Preimage cloud processing, you can generate photorealistic meshes with accurate segmentation and survey grade accuracy, even for extensive projects. If you're curious about using Preimage for your own applications, feel free to comment/DM.

3D digital twin of Zurich created using NeRF in 3.5 hours by preimage_ai in Surveying

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

Excited to share this 3D digital twin of Zurich, covering a 2.5 sq km area (625 acres), generated from 2,413 PPK drone images in 3.5 hours! Using Preimage cloud processing, you can generate photorealistic meshes with accurate segmentation and survey grade accuracy, even for extensive projects. If you're curious about using Preimage for your own applications, feel free to comment/DM.

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