Scene identification in news video by character region segmentation

Abstract

Reflecting the demand for recycling and retrieval of video, we are proposing an automatic indexing system for news video that considers correspondences between textual indices and image contents. In this paper, we focus on the background image content (i.e. scene) identification portion of the system. The analysis is performed by segmenting (human) character region from background region, and was applied to actual news video for evaluation. The overall result showed the effectiveness of the proposed method by 7 to 8%, and indicated that character existence itself is an important feature. Individual observation among various scenes indicated that multiple features should be combinatorily used according to each scene, and that the data set should be exponentially extended for higher performance.