Here is the first version of a simple droplet for converting and publishing 360 panoramic videos. It is intended to be used for the processed output file from a Ricoh Theta S that has the standard 1920×960 resolution. It is easy to do manually, but many people asked for an automatic droplet.
It conveniently includes 32-bit and 64-bit versions of FFMPEG for performing video conversion.
- Extract to your KRPano folder.
- Drag your MP4 video file to the ‘MAKE PANO (VIDEO FAST) droplet’.
- Be patient while your video is encoded to various formats.
- Rename the finished ‘video_x’ folder to a name of your choice.
You can download the droplet here:
Recent improvements include:
- Adding three variations of quality, which can be accessed by the viewer in Settings.
- Improving the quality of the default playback setting.
- Automatically switching to the lowest quality when used on a mobile device.
- Using a single .webm video, as the format is very rarely used, and very time consuming to encode.
- Outputs to a named folder.
So I did it myself, and made a Pull request (Github) with the official Laravel Elixir repository, which was approved. Nice to give back.
“A prototype 3D-printed robotic hand that can be made faster and more cheaply than current alternatives is this year’s UK winner of the James Dyson Award.” (BBC News link)
This is a fantastic idea, which has so much value to people without limbs. Bionic prosthetics can cost up to £100,000, and £30,000 for a single hand.
The 3D-printed robotic hand in the article costs £2,000, which is the same price as a prosthetic hook, and offers similar functionality to the top-of-the-range options.
The designer gets to develop his interest in creating a product, while helping the estimated 11 million people who are hand amputees worldwide.
I listened to an interesting podcast today, exploring the game Rock, Paper, Scissors, prediction patterns and game theory.
Being clever isn’t an effective way of winning, as people are rarely perfect decision makers. The Nash equilibrium is only relevant to domains with perfect decision makers. So it is important to consider the choices of others.
In the podcast, it was mentioned that from large datasets:
“The biggest chunk of people will think one step ahead, the next biggest chunk of people will think totally randomly, the next biggest chunk of people will think two steps ahead, and a small number of people will go beyond two steps.“
It also considers crowds and groups influencing decisions.
This project entitled “Large-Scale, Real-Time, Visual-Inertial Localization” is interesting, using Google’s experimental ‘Tango’ hardware to improve real-time tracking of location and position.
The hardware is a tablet computer with a motion tracking camera, a 4 megapixel 2µp pixel camera, integrated depth sensing and a high-performance processor. This equipment aids in tasks like scanning rooms. A limited number of kits were produced and given or sold to professional developers with the intent of making technological developments.
One day we may see more accurate and interesting augmented reality. I’ve often thought overlaying information onto our current reality would be interesting. Walking down a street and seeing for-sale signs could be interesting. It may just being overloaded in advertising, making a virtual eyesore though.
Get Out of My Lab: Large-scale, Real-Time Visual-Inertial Localization
Simon Lynen, Torsten Sattler, Michael Bosse, Joel Hesch, Marc Pollefeys and Roland Siegwart.
Autonomous Systems Lab, ETH Zurich
Computer Vision and Geometry Group, Department of Computer Science, ETH Zurich