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Rotisserie - ESports Streaming

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  • Jake Madden
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POSTED IN: Cognitive Wingman

Very cool.
Rotisserie - ESports Streaming - It's basically an "Obeserving Agent" to help provide SITUATIONAL AWARENESS in this virtual world. 

I'm very exicted about this work - because it it, as the core, a "Sensemaking System" that is Situationally Aware, and could be expanded FROM "Number of Players Alive" TO "Conversations or Relationships I care about; or Types of Drama / Interactions"  - which - a powerful "look here" tool to connect 1000+ Watchers to the dozen(s) Actors/Players.

 

Rotisserie

Rotisserie is a web application created by IBM developer advocates Cullen Taylor and Spencer Krum

https://rotisserie.tv/

https://github.com/IBM/rotisserie

"It features an always-exciting video stream of the extremely popular computer game Player Unknown's Battlegrounds. Rotisserie is written in Node.js. The current state of the application is limited to Twitch live streams.

It gets a list of live streams from Twitch then uses computer vision to determine the number of people alive. This page will show you the stream that has the least number of players alive in their match.

The application will watch streams in the background and determine which has the least number of players alive. This webpage will check periodically if it matches the best stream determined by the application and will seamlessly switch to that."

 

 

IBM Code Pattern

https://developer.ibm.com/code/patterns/implement-computer-vision-playerunknowns-battlegrounds-live-streams/

Implement computer vision for PlayerUnknown’s Battlegrounds live streams
Build a web app that uses OCR on live-streaming video platform Twitch

PUBG Rotisserie features a video stream of a player in the extremely popular multiplayer video game, PlayerUnknown’s Battlegrounds (PUBG). It performs optical character recognition (OCR) on the live streams found on Twitch to identify which streams have only a handful of players left and are close to the final moments of play. In this developer pattern, learn one of the many ways to implement computer vision to derive data from a video

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"Description On Twitch and other websites, professional and regular computer players live-stream their games. At any given time, thousands of people are streaming on Twitch, and hundreds of thousands of viewers are watching those streams.

PUBG is a first-person or third-person shooter game. One hundred players spawn on an island, searching for loot and killing other player’ characters. There are no re-spawns. Only one player or team can win. Think Hunger Games meets Battlefield. The problem is that part of this game is relatively boring.

Watching a streamer when close to winning (25 people or fewer left alive) is very exciting. But watching a streamer when there are 90 or even 50 people still alive is much less exciting. This developer pattern shows you one of the many ways to implement computer vision to derive data from a video. You will learn how to set up this application locally or in containers. You will also dive into deployment in Kubernetes, a container orchestration platform.

PUBG Rotisserie watches all the streams available on Twitch and switches between streams, showing the streams that are the most exciting. This can be left on a second monitor or on a TV in a lobby or sports bar.

Using computers to watch the entire streaming space for a game is a new thing only PUBG Rotisserie does right now. Using algorithms to switch between the streams like a virtual director is another innovative step"

 

Bravo Spencer and Cullen and team!

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About the Author

Ryan Anderson

Ryan Anderson

Hi! I like to play with data, analytics and hack around with robots and gadgets in my garage. Lately I've been learning about machine learning.

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Cognitive Wingman - Never Walk Alone

Created: December 20, 2016

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