{"title":"The Future-Viewer visual environment for semantic characterization of video sequences","authors":"M. Campanella, R. Leonardi, P. Migliorati","doi":"10.1109/ICIP.2005.1529974","DOIUrl":null,"url":null,"abstract":"In this paper we address the problem of semi-automatic annotation of audio-visual sequences. Specifically, we propose the use of an innovative graphic framework, named Future-Viewer, to perform a quick and efficient annotation of a given multimedia document. The basic idea consists in visualising a 2-dimensional feature space in which the shots of the considered video sequence are located. In this window, shots with similar content fall near each other, and the proposed tool offers various functionalities for automatically and semi-automatically finding and annotating the shot clusters in such feature space. The proposed system has been used to analyze the content in terms of logical story units of few video sequences and the obtained results appear very interesting.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Image Processing 2005","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2005.1529974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper we address the problem of semi-automatic annotation of audio-visual sequences. Specifically, we propose the use of an innovative graphic framework, named Future-Viewer, to perform a quick and efficient annotation of a given multimedia document. The basic idea consists in visualising a 2-dimensional feature space in which the shots of the considered video sequence are located. In this window, shots with similar content fall near each other, and the proposed tool offers various functionalities for automatically and semi-automatically finding and annotating the shot clusters in such feature space. The proposed system has been used to analyze the content in terms of logical story units of few video sequences and the obtained results appear very interesting.