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.
|Titolo:||An Unsupervised Algorithm for Anchor Shot Detection|
|Data di pubblicazione:||2006|
|Appare nelle tipologie:||4.1.1 Proceedings con DOI|