计算机应用研究2018，Vol.35Issue(3)：926-929,4.DOI:10.3969/j.issn.1001-3695.2018.03.060
基于时空域深度特征两级编码融合的视频分类
Video classification based on cascaded encoding fusion of temporal and spatial deep features
摘要
Abstract
To solve the problem of low performance of deep features used for video classification,this paper proposed a novel method based on the fusion of video temporal and spatial information with two-level encoding method.Firstly,it used two convolutional neural networks (CNN) to respectively extract the video's spatial and temporal information.Then encoding the spatial and temporal information with Fisher vector (FV) and locally aggregating method respectively to get the effective representation of video.Finally,based on the two-level cascaded fusion feature,it used support vector machine (SVM) to classify the videos.Experimental results on UCF101 show that their method has a better performance contrasting to the state of the art methods.关键词
视频分类/两级编码/深度学习/特征融合Key words
video classification/cascaded encoding/deep learning/feature fusion分类
信息技术与安全科学引用本文复制引用
智洪欣,于洪涛,李邵梅..基于时空域深度特征两级编码融合的视频分类[J].计算机应用研究,2018,35(3):926-929,4.基金项目
国家自然科学基金资助项目(61521003,61379151) （61521003,61379151）
科技支撑计划资助项目(2014BAH30B01) （2014BAH30B01）
河南省杰出青年基金资助项目(144100510001) （144100510001）
国家杰出青年科学基金资助项目(61601513) （61601513）
