Rotisserie is a web application created by IBM developer advocates. 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.
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.
Implement computer vision for PlayerUnknown’s Battlegrounds live streams
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Created: July 25, 2014Englishfrançais