PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Exploiting temporal and inter-concept co-occurrence structure to detect high-level features in broadcast videos
Ville Viitaniemi, Mats Sjöberg, Markus Koskela and Jorma Laaksonen
In: WIAMIS 2008, Klagenfurt, Austria(2008).


In this paper the problem of detecting high-level features from video shots is studied. In particular, we explore the possibility of taking advantage of temporal and interconcept co-occurrence patterns that the high-level features of a video sequence exhibit. Here we present two straightforward techniques for the task: N-gram models and clustering of temporal neighbourhoods. We demonstrate the usefulness of these techniques on data sets of the TRECVID high-level feature detection tasks of the years 2005-2007.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Information Retrieval & Textual Information Access
ID Code:4359
Deposited By:Ville Viitaniemi
Deposited On:13 March 2009