Searching Live Meeting Documents "Show me the Action"

Abstract

Live meeting documents require different techniques for effectively retrieving important pieces of information. During live meetings, people share web sites, edit presentation slides, and share code editors. A simple approach is to index with Optical Character Recognition (OCR) the video frames, or key-frames, being shared and let user retrieve them. Here we show that a more useful approach is to look at what actions users take inside the live document streams. Based on observations of real meetings, we focus on two important signals: text editing and mouse cursor motion. We describe the detection of text and cursor motion, their implementation in our WebRTC (Web Real-Time Communication)-based system, and how users are better able to search live documents during a meeting based on these extracted actions.