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https://github.com/benfoxall/jumbotron
https://github.com/benfoxall/jumbotron
Last synced: 16 days ago
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- Host: GitHub
- URL: https://github.com/benfoxall/jumbotron
- Owner: benfoxall
- License: mit
- Created: 2014-06-01T19:15:16.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2014-09-22T20:59:34.000Z (over 10 years ago)
- Last Synced: 2025-01-19T08:31:12.152Z (23 days ago)
- Language: JavaScript
- Size: 1.09 MB
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# NOTE - this is in no way complete
**Currently it gives a few helper functions for interacting with js-aruco output.**
---
# jumbotron
## libraries
* https://github.com/jcmellado/js-aruco
* http://sylvester.jcoglan.com/
(not used, but could be useful)
* https://github.com/calvinfo/socket-ntp
* https://help.pubnub.com/entries/24122123-How-do-I-Synchronize-Multiple-Devices-
## usage
steps
1. master creates room
2. clients register as being part of the room, display markers
3. master observes clients
4. master closes room, notify clients of world
```js
// mid-level api - recognition
// potentially call several times to observe different angles + new markers
jumbotron.observe(imagedata)
// calculate the world dimensions, and positions of each marker
jumbotron.construct();
// -> {width: 2000, height: 3000, markers: [{id: 32, transform: […]}]}
// get going
jumbotron.start();
```
---
# Development
This should only matter if you are hacking on the internals and fixing stuff (which would be very appreciated).
## Setup
Dependencies are managed by [bower](http://bower.io/), install them with:
```bash
bower install
```
Then you need to serve the files through a web server. [SimpleHTTPServer](https://docs.python.org/2/library/simplehttpserver.html#module-SimpleHTTPServer) is a pretty easy way to do that
```bash
python -m SimpleHTTPServer
```
Then visit [localhost:8000](http://localhost:8000) - most interesting stuff is in the /hacks folder.
## recognition approach
The marker recognition is performed by [js-aruco](https://github.com/jcmellado/js-aruco). The [pose estimation](https://github.com/jcmellado/js-aruco#3d-pose-estimation) component requires the physical size of the marker, which we don't have. Instead, we use the constraint that all markers lie on the same plane to work out their positions relative to each other. Also, by approaching it this way - it allows us to combine several observations cover larger areas and also handle observations with missing markers.
```js
// the structure of marker output from js-aruco
[
{id:a, corners:[/*pixel coords*/]},
{id:b, corners:[/* ... */]}
]
```
The first step is to work out the relative positions from the context of each marker (where the other markers have been transformed to make the marker a 1×1 square positioned at 0,0).
From this, we build a 'relative vector grid', which stores observations between markers.
```js
{
'a-b':[[2,2]],
'b-a':[[-2,0]]
}
```
We then take this to build a representation of the markers in an arbitraty space. The current approach is to cycle through observations:
* first item becomes the base for the rest of the space
* any linked markers are translated based from that marker
* any existing marker is scaled, rotated based on it's own view of other markers
Which should end up with something like:
```js
{
a: [[1,0,0],[0,1,0],[0,0,1]], // identity
b: [/* rotate(-45) translate(2,2) scale(2) */],
}
```
---
resolves [benfoxall/benfoxall.github.com#16](https://github.com/benfoxall/benfoxall.github.com/issues/16)