Weighted Block Matching-Based Anchor Shot Detection with Dynamic Background
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Unsupervised event segmentation of news content with multimodal cues
Proceedings of the 3rd international workshop on Automated information extraction in media production
A unified scheme of shot boundary detection and anchor shot detection in news video story parsing
Multimedia Tools and Applications
Anchor shot detection with diverse style backgrounds based on spatial-temporal slice analysis
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Style learning based story boundary detection for Chinese broadcast news videos
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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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.