Steuart Systems

This 3D model includes alignment errors……. and we know how to fix them. Our objective is to develop an automatic 3D model creation system, and we know from experience that the errors will get smaller as our calibration process is refined. Below is a description of how this model was made using images from Proto-4F of our 8-camera 3D-360 scanner.

A 3D model requires images from multiple perspectives, so for this model we scanned from 4 different locations: two scans from a high perspective with the scanner cameras at 6 feet, and two low scans with the scanner 3 feet above the floor. Once the scans were completed (all of the pictures have been taken and downloaded) the images from the 4 scans were processed using our automatic 3D reconstruction software. This processing resulted in 4 “point clouds” of 3D data: one point cloud for each scan. Next the 4 point clouds were aligned with each other to create a single “point cloud” of, in this case, 20 million points.

Point clouds are a precise, but inefficient way to format and store 3D data. Point clouds for 3D data can be compared to the BMP format for 2D images. Just as compressed JPEGs are about 10x more efficient than uncompressed BMPs for storing 2D images, triangular meshes are a more efficient way to store 3D data than uncompressed point clouds. Meshes are efficient because a group of 3 points for a single triangle can replace thousands (or millions) of points if the points are in a plane. Decades of work from people around the world has resulted in mature procedures to generate meshes from point clouds. Our current meshing routine turned the 400 Mbyte “point cloud” of 20,000,000 points into a 20MB mesh of 24,000 triangles. In the future we will use more efficient meshing procedures that produce better meshes with even fewer triangles.

After meshing we have a 3D model of the area that was scanned, but at this point the mesh is not photorealistic. We make the model photorealistic by “projecting” the original color images taken during the scanning process onto the mesh. This automatic process is called “texture projection,” and when it is done well it results in a photorealistic 3D model.

Texture projection works very well when everything is correctly aligned and registered, but alignment errors can rapidly build on each other and produce errors that make a model look bad. The alignment errors in this process come from several different sources in the calibration/scanning/processing pipeline:

– Lens distortion correction errors inside each camera
– Alignment errors between the left and right camera in each of the 4 pairs of cameras
– Alignment errors between each of the 4 pairs of cameras
– Alignment errors between the 4 scans

These are all well defined problems that we are working on. We could proceed slowly and reduce the errors by recalibrating the existing Proto-4F 3D-360 camera system. This approach would take weeks and it could cut the errors in half a few times, but it cannot correct the built-in limitations of our current lenses and calibration facility.

Another option is to build on our two plus years of experience with the Proto-4x family and design a new Proto-5x series. The new design will have more lenses, higher resolution sensors, faster processors (ARM/AMD Fusion/Tegra/FPGA/other?), and it will be calibrated with a 10x larger “calibration bunker.” I am currently working on Proto-5x designs, and a key characteristic may be to increase the number of cameras from the current 8 to 32, or even as many as 100. A large array of inexpensive lenses can cost less and outperform a small number of expensive lenses. The trick is to design a manufacturable and and inexpensive array of sensors, lenses and processors. While a design with up to 100 camera may sound extravagant, remember that the fly’s eyes have over 1,000 lenses:

Because Proto-5x will require the design, layout, fabrication and testing of a new camera/processor board, this approach will take at least four months. Software porting, calibration, and testing could add another 4 to 8 months to the process. Depending on the final design, the Proto-5x family could reduce the errors by a factor of 10 or more.

The cameras are finally calibrated, and the communications and power systems are installed and working. Now I can finally begin producing scans to test and fine tune the software.

Today I scanned part of the lab, and the animated GIF illustrates the 3D nature of the scan. When producing a 3D model, multiple perspectives must be captured to fill in occlusions (blind spots). For this model, three scans from different locations were merged to produce a point cloud. The GIF consists of 7 different screen-shots of the point-cloud. While there are still occlusions, many have been filled. For example, notice that you can see both above and below the table.

The original 32-bit software that we use to turn pictures into 3D models is almost 5 years old, and it runs on 32-bit Windows XP. The old software often crashes when processing high resolution images because the 2GB memory limit isn’t enough to process the gigabytes of data that our scanner can quickly produce. Today’s scan was made on a computer running 64-bit Windows 7, and we are currently replacing the old 32-bits software with more advanced 64-bit code. The new software runs much faster in 64-bit mode because it can keep temporary files in RAM instead of writing them to and reading them from a slow disk. Even using a Solid State Drive (SSD) wastes minutes of unnecessary processing.

COMING UP: Much better scans processed by SketchUp & posted into Google Earth.

Four buildings that we have recently uploaded

We can now create 3D buildings and place them into Google Earth. The results can be viewed with a normal web browser, and we are exploring how to take advantage of this new low cost form of web promotion. Creating 3D models for Google Earth is a useful capability that we intend to continue refining, and we will begin offering the service of modeling local buildings and placing them into Google Earth. Click here to go to Purcellville Virginia and see one of our 3D model on Google Maps. Use the left, right, and center mouse buttons for navigation.

Here is an overview of how to put images onto Google Earth. The program Google SketchUp can be used to create photorealistic 3D models of real buildings. Once a model is built it can be uploaded to Google for possible placement into Google Earth. A model is integrated into Google Earth only after a reviewer decides that it satisfies all of Google’s acceptance criteria. Our early efforts were rejected for reasons like being too big, being too complex, or for exhibiting “Z-fighting.” At times we have experienced delays of over four weeks during the review process, but after nearly three months of effort we have learned how to efficiently make models that Google will accept and place into Google Earth.

While creating 3D content for Google Earth is interesting, our main objective is to build a practical 3D-360 photorealistic scanner. Prototype-4E is in the final stages of assembly, and this July we plan to begin using it to create photorealistic interiors for our 3D models. When the results are good enough we plan to use SketchUp and Google Earth to demonstrate the ability to create models that you can walk around and also into. Once inside you will see detailed photorealistic interiors that are too complex to model with most traditional techniques.

From June 11 to 13 Google hosted a 3-day training called SketchUp Basecamp. About 400 people from all over the world all gathered to learn about the 3D visualization techniques of SketchUp and how to integrate the 3D models into Google Earth. We spent most of our time on this patio and in the buildings that you see.

Inspired by Google’s global perspective, I decided to make a Google-centric version of a “Google Earth.” I stiched 18 images together to make a spherical panorama, and then warped the image to form a globe. This is a first draft, and I plan to post a better HDR version without the tripod and shadow once I get back home.

The stitching errors have been removed, and HDR & tone mapping have improved the details. There will probably be a V6 with a few more tweaks. A little more sky would be nice, and there are some HDR artifacts in the lower left.

54 shot panoramic HDR.
3 sets of 18: -2, 00, +2

This hodgepodge of cameras, epoxy, and even duct tape was was used to develop 3D scanning software. After the research (late 2007) it was dissasembled and 7 of the 8 Canon 5Ds (I kept one =:-) were sold on E-bay. A much improved Prototype 4B with 10 custom cameras and lenses will allow a new phase of development in early 2009.