Fish4Knowledge Pavilion and Underwater Gallery in OpenSim

The Fish4Knowledge Virtual World Gallery and Underwater pavilion was originally created in Second Life but has now been replicated on the OpenSimulator-based Openvue grid and OSGrid. OSGrid provides free avatar to anyone so is a good way to visit the facility and see the displays about the project.

F4K on Openvue
F4K on Openvue

A single user “Fish4Knowledge Virtual Reality Experience” is also available in Unity3D. More details below.

Fish for Knowledge Access in Second Life and OpenSim

The F4K facilities can be accessed in several virtual worlds locations:

F4K on OSGrid F4K on OSGrid

VR using the Oculus Rift in Second Life and OpenSim

Oculus Rift Virtual Reality views can be obtained using the CtrlAltStudio Viewer
2015-10-20-OpenSim-F4K-Rift-1 2015-10-20-OpenSim-F4K-Rift-2

Fish4Knowledge Virtual Reality Experience – VR using the Oculus Rift in Unity3D

The OpenSim F4K and Edinburgh region build in OpenSim has been exported via an OpenSim Archive (OAR) file and converted by Fumi Hax’s OAR-Converter tool to Collada (DAE) meshes suitable for importing into Unity3D. More details of the process and some images from the Unity3D experience can be found at…

https://blog.inf.ed.ac.uk/atate/2015/10/24/opensim-oar-convert-to-unity-scene-with-windows-interface/.

The Fish4 Knowledge experience in Unity3D web player, or the download of a standalone version for Windows and that works with 2D screens or in VR in the Oculus Rift is available at…

http://www.aiai.ed.ac.uk/~ai/unity/oarconv/Edinburgh-F4K/

Reference

Chen-Burger, Y-H. and Tate, A. (2015) The Fish4Knowledge Virtual World Gallery, in Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data (Fisher R.B., Hardman, L., Lin, F.P., Giordano, D. and Chen-Burger, Y-H. eds.), Chapter 17, pp. 245-252, October 2015, Intelligent Systems Reference Library, Springer.

This entry was posted in OpenSim, Virtual World and tagged , , , , , , , , , . Bookmark the permalink.

2 Responses to Fish4Knowledge Pavilion and Underwater Gallery in OpenSim

  1. chris says:

    I stumbled across your article as I have a keen interest in oceanography. I was fascinated to learn that the camera documented in fish4knowledge was able to identify in total 14 million species of fish. We really live in wonderful times! I wonder if the fish know your watching lol?

  2. bat says:

    @Chris… the number of SPECIES found was not that many 🙂 Reports from the project indicated that they saw 1.4 billion fish during the experiment with 100Tb of data recorded amounting to 90,000 camera hours of video.

    Prof. Bob Fisher of the F4K project confirmed some of the numbers and details related to fish species observed…

    Hi – we eventually found (by hand) about 50 of the 3000+ species typical to the Taiwan sea. Many of the species that we did not see were: too small, come out at night, live deeper than the cameras, etc. Our final species recognition module had 23 species, covering more than 99% of all of the observed fish. The distribution of observations is greatly unbalanced, with the top single species (Dascyllus reticulatus) accounting for 40% of the observations. The top 15 account for about 97%. Part of the reason for the unbalance is that the top 4 species are ‘resident’, ie. have a home area and stay near there. So, if you see an individual once, you’re highly likely to see it many times.

Comments are closed.