PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Rushes summarization with Self-Organizing Maps
Markus Koskela, Mats Sjöberg, Jorma Laaksonen, Ville Viitaniemi and Hannes Muurinen
In: TRECVID Workshop on Video Summarization (TVS'07), Augsburg, Germany(2007).

Abstract

In this paper, we describe our approach for video summarization that was applied to the BBC rushes material as part of the TRECVID 2007 evaluations. The method consists of initial shot boundary detection followed by shot similarity assessment and pruning, with both stages implemented using multiple parallel Self-Organizing Maps and within our content-based multimedia information retrieval and analysis framework named PicSOM. The results indicate that our approach can be successfully applied to rushes summarization. Compared to other submissions, our method resulted in the overall shortest summaries with close to median performance in the fraction of ground-truth inclusions found.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Multimodal Integration
Information Retrieval & Textual Information Access
ID Code:3293
Deposited By:Ville Viitaniemi
Deposited On:07 February 2008