Work:

A-Frame.io is a free and open source JS library from Mozilla for creating VR experiences. It's incredibly simple to use.  After calling the script, available here:

Loading and placing a textured 3D scene is as simple as this:

         
                 
                 
         
 

I wanted to use A-Frame.io to share scans from the MatterPort Scenes app. Unfortunately, while A-Frame supports 3D content, it only supports textured meshes, not the color point clouds that the Matterport app produces. So I needed to turn a collection of colored dots, into a 3D polygon and a series of colored triangles. After some research, I discovered a workflow for doing that in MeshLab. 

Following this tutorial, with some difficulty, ( I need to figure out the Undo function in MeshLab, and I seem to run into a problem that requires an occasional relaunch if I miss a step ) I managed to transform a series of point-cloud-based scans into Meshes. To be specific .OBJ files with .PNG textures. Here's a video of one result: 

I've made two full demos available, THE FIRST SCENE includes two rooms from the WhiteHouse at Christmas time and our team around a McClatchy Board Room. THE SECOND SCENE is my apartment around Thanksgiving. Both scenes are scanned in several chunks in the Thanksgiving scene I've tried to bring the chunks seamlessly together.

*The files in these pages are not optimized, neither is the loading process, so be patient while the A-Frame demos load. You may even need to refresh a few times. 

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Next Steps

• Get to know MeshLab better
• Find Open Source way to share a Point Cloud, perhaps POTREE.
  • DONE: See Iteration 4

Feedback

• TBD

Work:

Here are two practice scans of the dress Rosa Parks was carrying that historic day she, when she was arrested for riding in front of  bus.

The two scans illustrate a problem with the MatterPort Scenes. In the image on the left, I tried to move around the dress and spatial drifting occurred. The phone lost its place and so it started to re-record the same points in different places. It's very pronounced in this image which was recorded through a reflective surface, but even when scanning plain opaque surfaces, there is a loss of clarity if you do multiple passes. The image on the right, by contrast, was produced with the phone sweeping over the dress only once, from a single perspective. The result is a 3D image with less noise and increased clarity. However the depth is limited. The recorded image is essentially a shell. 

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Next Steps

• Compare to photogrammetry for clarity and ease of use.
• Look for App improvements or better apps
• Investigate a post-processing solution
• Investigate a workflow that combines multiple shells into a full 3D image.

Feedback

• None Yet

Work:

I started scanning using an app called Real-Time Appearance-Based Maps, but found it buggy at best.

Then I discovered the more polished MatterPort Scenes App. The App creates a 3D model using Tango's structured light sensor. It basically bounces infrared light off of a surface to determine how far a given point is from the lens. It then colors that point using the wide angle lens, and begins establishing a cloud of these points in 3D, as you move through space and turn the phone, the app progressively adds more points. The resulting file is called a point cloud.

Here's a gif of the first point cloud I made:

File sharing isn't fully supported in the app but it's possible to export the model as a .PLY or Polygon File Format formatted as binary_little_endian 1.0. 

After a bit of research, I discovered a free and powerful cross-platform application called MeshLab that allows me to open and manipulate the file. The GIF above is a screen record of MeshLab

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Next Steps

• Get more practice scanning
• Figure out the best way to deliver the resulting files to an audience
• Find more apps

Feedback

None yet