Crowdsourcing Event Detection in YouTube Videos
Venue
Detection, Representation, and Exploitation of Events in the Semantic Web (DeRiVE 2011), Bonn, Germany
Publication Year
2011
Authors
Thomas Steiner, Ruben Verborgh, Rik Van de Walle, Michael Hausenblas, Joaquim Gabarro
BibTeX
Abstract
Considerable efforts have been put into making video content on the Web more
accessible, searchable, and navigable by research on both textual and visual
analysis of the actual video content and the accompanying metadata. Nevertheless,
most of the time, videos are opaque objects in websites. With Web browsers gaining
more support for the HTML5 <video> element, videos are becoming first class
citizens on the Web. In this paper we show how events can be detected on-the-fly
through crowdsourcing (i) textual, (ii) visual, and (iii) behavioral analysis in
YouTube videos, at scale. The main contribution of this paper is a generic
crowdsourcing framework for automatic and scalable semantic annotations of HTML5
videos. Eventually, we discuss our preliminary results using traditional
server-based approaches to video event detection as a baseline.
