In this paper we present a novel algorithm for anchor shot detection (ASD). ASD is a fundamental step for segmenting news video into stories that is among key issues for achieving efficient treatment of news-based digital libraries. The proposed algorithm firstly uses a clustering method for individuating candidate anchor shots and then employs a two-stage pruning technique for reducing the number of falsely detected anchor shots. Both clustering and pruning are carried out in an unsupervised way. The algorithm has been tested on a wide database and compared with other state-of-the-art algorithms, demonstrating its effiectiveness with respect to them.

An Unsupervised Algorithm for Anchor Shot Detection

DE SANTO, Massimo;FOGGIA, PASQUALE;PERCANNELLA, Gennaro;VENTO, Mario
2006-01-01

Abstract

In this paper we present a novel algorithm for anchor shot detection (ASD). ASD is a fundamental step for segmenting news video into stories that is among key issues for achieving efficient treatment of news-based digital libraries. The proposed algorithm firstly uses a clustering method for individuating candidate anchor shots and then employs a two-stage pruning technique for reducing the number of falsely detected anchor shots. Both clustering and pruning are carried out in an unsupervised way. The algorithm has been tested on a wide database and compared with other state-of-the-art algorithms, demonstrating its effiectiveness with respect to them.
0-7695-2521-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/1517781
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