A Multi-Stage Approach for News Video Segmentation Based on Automatic Anchorperson Number Detection

Abstract

In this paper we present an algorithm for anchor shot detection that is a fundamental step for segmenting news video into stories. This is among key issues for achieving efficient treatment of news-based digital libraries. The proposed algorithm creates a set of audio/video templates of anchorperson shots in an unsupervised way, then classifies shots by comparing them to all the templates when there is one anchor and to a single best template when there are two anchors. In this paper we also propose an automatic selector, based only on the audio track, that is able to classify a news video as presented by one or two anchorpersons. The method has been tested on a wide database demonstrating its effectiveness.