Content-Based Video Tagging for Online Video Portals

Adrian Ulges, Christian Schulze, Daniel Keysers, Thomas Breuel
MUSCLE/ImageCLEF Workshop 2007, Vienna, Australia, Vienna University of Technology, 9/2007
Online Proceedings only


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 We show that a combination of several visual features improves performance over our baseline system by about 30%.




@misc{ ULGE2007,
	Title = {Content-Based Video Tagging for Online Video Portals},
	Author = {Adrian Ulges and Christian Schulze and Daniel Keysers and Thomas Breuel},
	BookTitle = {MUSCLE/ImageCLEF Workshop 2007},
	Note = {Online Proceedings only},
	Month = {9},
	Year = {2007},
	Organization = {Vienna University of Technology}

Last modified:: 30.08.2016