Immersive Visualization / IQ-Station Wiki
This site hosts information on virtual reality systems that are geared toward scientific visualization, and as such often toward VR on Linux-based systems. Thus, pages here cover various software (and sometimes hardware) technologies that enable virtual reality operation on Linux.
The original IQ-station effort was to create low-cost (for the time) VR systems making use of 3DTV displays to produce CAVE/Fishtank-style VR displays. That effort pre-dated the rise of the consumer HMD VR systems, however, the realm of midrange-cost large-fishtank systems is still important, and has transitioned from 3DTV-based systems to short-throw projectors.
Toirt Samhlaigh
Toirt Samhlaigh (Gaelic for "Volume Visualizer") is a virtual reality volume rendering (and other visualization techniques) tool — VR-VR written using the Vrui VR integration library. Patrick O'Leary began writing it in 2007 at The Desert Research Institute where it was first deployed in the DRI 4-sided CAVE, and from time to time has been updated to continue operating in more modern systems.
It was inspired by both the Crumbs CAVE visualization tool from NCSA/UIUC (1995), and the Simian Volume Renderer from Joe Kniss et al. at Utah and LANL (2001).
Software
The Toirt Samhlaigh tool is available on github.com though the primary repository remains written for a very old version of the Vrui VR library. Two forks of this repo have been used to make minor updates for newer versions of Vrui. There is also a newer version updated for Vrui 12.1 that is currently in the works that will be added as an additional fork.
Running Toirt Samhlaigh
Command-Line Arguments
Toirt Samhlaigh has a handful of command line options that are used to load data into the application:
| Option | Affect |
|---|---|
| -file <filename> | Load the given file into the application as a scalar dataset |
| -redFile <filename> | Load the given file into the red-channel of an RGB vector dataset |
| -greenFile <filename> | Load the given file into the green-channel of an RGB vector dataset |
| -blueFile <filename> | Load the given file into the blue-channel of an RGB vector dataset |
| -size <X> <Y> <Z> | Specify the 3 dimension sizes of the data |
| -scale <X> <Y> <Z> | Relative scales of the 3 dimensions of the data |
| -sliceFactor <X> <Y> <Z> | Slice spacing, based on minimum x,y,z delta between slices — e.g. value of 0.4 would draw 2.5 slices per voxel |
| -textureSize <value> | Size of 3D texture block. changes from card to card for performance — each texture block is a OcTree root |
| -leafSize <value> | What is the smallest dimension of a leaf (smaller leafs create large (slower) data structures) |
| -ratioOfVisibilityThreshhold <value> | Value used for visibility refinement — if less than this value, don't proceed down OcTree |
| -rootSection <config-section> | The Vrui option used to select a particular configuration |
- A note about the size and scale option arguments: the order of how the the sizes within raw data files is rather odd (or at least unexpected). For example, for data converted to raw from a TIFF image stack has the order X,Y,image-number, which is translated into -size Y x img-num x X.
Datafile formats
Several types of datafiles are accepted for the <filename> arguments:
| Extension | Type |
|---|---|
| .vol | unsigned 8-bit (byte) volume data format |
| .fvol | floating point volume data |
| .dat | 16-bit data per voxel |
| .segy | Society of Exploration Geophysisists Y format (aka “.seg”) |
| .nlv | “Nick Lancaster Volume” (Specialty format) |
| .raw | unsigned 8-bit (byte) raw bytes of data (also .raw.r, .raw.g & .raw.b) |
| .raw16 | unsigned 16-bit (byte) raw bytes of data |
| .raw32 | unsigned 32-bit (byte) raw bytes of data |
Run-time options
(To be added)
See Also
Here are some other resources for the Toirt Samhlaigh tool:
- Toirt Samhlaight on github (for older version of Vrui)
- Immersive Visualization and Interactive Analysis of Ground Penetrating Radar Data (Conference Paper)
- RSVP: Remote Sensing Visualization Platform for Data Fusion (Conference Paper)
- Immersive Visualization for the Geological Sciences (Book Chapter)