Title :
An Unsupervised Algorithm for Anchor Shot Detection
Author :
De Santo, M. ; Foggia, P. ; Sansone, C. ; Percannella, G. ; Vento, M.
Author_Institution :
Dipt. di Ingegneria dell´´Informazione ed Ingegneria Elettrica, Univ. degli Studi di Salerno, Fisciano
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 effectiveness with respect to them
Keywords :
image segmentation; object detection; pattern clustering; video signal processing; anchor shot detection; clustering method; news video segmentation; news-based digital library; pruning technique; unsupervised algorithm; Cameras; Clustering algorithms; Clustering methods; Databases; Gunshot detection systems; Partitioning algorithms; Software libraries; Testing; Variable speed drives; Video sharing;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.266
