Publication
Content-Based Video Tagging for Online Video Portals
Adrian Ulges; Christian Schulze; Daniel Keysers; Thomas Breuel
9/2007.
Abstract
Despite the increasing economic impact of the online video market, search in commercial
video databases is still mostly based on user-generated meta-data. To complement this
manual labeling, recent research efforts have investigated the interpretation of the visual
content of a video to automatically annotate it. A key problem with such methods is the
costly acquisition of a manually annotated training set.
In this paper, we study whether content-based tagging can be learned from user-tagged
online video, a vast, public data source. We present an extensive benchmark using a
database of real-world videos from the video portal youtube.com. We show that a combination
of several visual features improves performance over our baseline system by about 30%.