计算机应用与软件2012，Vol.29Issue(12)：10-12,26,4.DOI:10.3969/j.issn.1000-386x.2012.12.003
基于多特征距离学习的视频分类
VIDEO CLASSIFICATION WITH MULTIPLE FEATURE DISTANCE LEARNING
摘要
Abstract
Video classification plays a significant role in video retrieval and content analysis. Multi-modal video features like audio, static image features and video motion features, etc. have been widely used in video classification, therefore how the multiple video features could be optimally combined to improve the video classification performance has become an important research topic. In this paper we propose an LI regularised distance learning model to study the subject of improving video semantic annotation performance with multiple features combination. The model gains the capability of an optimal combination of the selected multiple video features due to the LI norm regularisation term is introduced. Experiments show that our approach substantially improves the performance of video classification on universal Columbia Consumer Video (CCV) video dataset.关键词
视频检索/视频分类/距离学习Key words
Video retrieval/Video classification/Distance learning分类
信息技术与安全科学引用本文复制引用
李真超,纪传俊,林哲,周向东,施伯乐..基于多特征距离学习的视频分类[J].计算机应用与软件,2012,29(12):10-12,26,4.基金项目
国家自然科学基金项目(61073002). （61073002）
