Steuart Systems

Photorealistic Digital 3D Model Creation

Omnidirectional Scene Acquisition IEEE Research Paper

Digital 3d/360 Degree Camera System Patent

How can you evaluate photogrammetry software and the 3D models that it creates? Switzerland’s ETH Institute of Technology (some rankings place ETH 4th in the world for engineering and technology) has developed a 25-part benchmark to evaluate photogrammetry software like ours. We have reason to believe that our results will be very strong.

The purpose of this post is to dust off our web site and say “get ready.” Our software’s ETH benchmark results should be posted this week. Soon after that we will release a 1.0 version of our OpenSource software MeshroomCL.

The Steuart Systems photorealistic 3D scanner uses hardware & software to produce 3D models, but how good is our software? We used the ETH 3D benchmark to evaluate it. We were hoping to be in the top 10% of the 116 entries from around the world, and the March 31 2022 benchmark result put us at #1. Some other group will claim the top spot eventually, but for now the ranking proves that our approach is world-class.

Good software is nice, but camera hardware is our main strength. Over the years our tests have shown that high-quality low-noise HDR images from our camera hardware amplifies the power of whatever software we use. Low-noise 3D content looks better, and it is easier to compress, distribute and view on the web.

Stay tuned. Over the next few weeks we will post results as we tune our software and our array of 32 cameras.

Garbage in
Garbage out

It is amazing that 3D models can be created from regular (uncalibrated) pictures. This link shows some nice examples of how uncalibrated images can be used to make 3D models.

Quality in
Quality out

Our approach is harder, but our results are better. We precisely calibrate our cameras, and we use the calibrated pictures to make 3D models.  As our calibration improves, our 3D models improve. The combination of better calibration and sub-pixel processing has allowed us to create models that are accurate to within 1 or 2 millimeters at 10 feet. Also, our new color processing routine adjusts lighting and allows the colors in different 3D scans to blend better. More accurate scan geometry and better color control results in better looking 3D models. The video below demonstrates our latest improvments. The complete 3D model in our video consists of 13 scans from 13 different locations.

I believe that we have tackled the hardest part of the problem: calibration.  Now that our geometry is correct, we can focus on making our 3D models attractive and easy to work with.  We will continue improving the system in the following three ways:

1) FASTER HARDWARE
We are finalizing the Proto-5B design. The current system takes about 7 minutes to create a single scan, and the next iteration of our scanner will capture the imagery at least 20 times faster.  ETA for this system is April 2016.

2) IMPROVED PHOTOREALISM WITH POST-PROCESSING
Post-processing imagery is normal. Photoshop is often used to clean up 2D pictures, and many 3D programs can clean up our 3D data. We are evaluating several programs, and will make our data work with the best solution(s).

3) INCREASED COMPATIBILITY WITH EXISTING 3D STANDARDS
Make it easier to move our data to other software like Unity, Meshlab, SketchUp, and possibly Matterport. Being compatible with Unity will make us compatible with headsets like Oculus, and that will allow a photorealistic 3D VR experience.

Here is an example of our latest results after a few more weeks of tuning the noise reduction controls. Now that most artifacts and distortion are sufficiently reduced, we will begin merging scans to produce larger models.

We have  steadily improved our scanning results over the last 6 weeks by modifying hardware, writing new software, and tuning over a dozen variables.  The video below demonstrates the effect of our enhanced noise reduction:

Low noise in 3D models is important for two reasons:

1. Low noise 3D looks better.  
2. Low noise 3D models are easier to compress & display.  In many cases smoothing should allow us to reduce a scan to less than 1% of the original size.

Noise reduction & smoothing has been around for decades, but there is a delicate balance between appropriate smoothing, and over-smoothing which can make objects look like jelly beans.  Our past experience with generic smoothing routines has been disappointing because they often round edges & eliminate important details. 

Why Our Smoothing Is Better Than Other Options

Instead of applying generic smoothing filters to our data after the 3D data has been created, we apply smoothing during the creation of 3D data.  We can achieve an optimal level of smoothness because our smoothing software has intimate knowledge of the scanner hardware and configuration.  Stereo scanners like ours can be accurate to a fraction of a millimeter up close, but precision falls off as the distance from the scanner increases.  Our smoothing routines use this fact to smooth our 3D data with more finesse.