Semantic Feature Mining for Video Event Understanding
文献类型：期刊论文
| 作者 | Yang, Xiaoshan ; Zhang, Tianzhu; Xu, Changsheng
|
| 刊名 | ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
 |
| 出版日期 | 2016-08-01 |
| 卷号 | 12期号:4页码:55:1-55:22 |
| 关键词 | Video Recognition Event |
| DOI | 10.1145/2962719 |
| 文献子类 | Article |
| 英文摘要 | Content-based video understanding is extremely difficult due to the semantic gap between low-level vision signals and the various semantic concepts (object, action, and scene) in videos. Though feature extraction from videos has achieved significant progress, most of the previous methods rely only on low-level features, such as the appearance and motion features. Recently, visual-feature extraction has been improved significantly with machine-learning algorithms, especially deep learning. However, there is still not enough work focusing on extracting semantic features from videos directly. The goal of this article is to adopt unlabeled videos with the help of text descriptions to learn an embedding function, which can be used to extract more effective semantic features from videos when only a few labeled samples are available for video recognition. To achieve this goal, we propose a novel embedding convolutional neural network (ECNN). We evaluate our algorithm by comparing its performance on three challenging benchmarks with several popular state-of-the-art methods. Extensive experimental results show that the proposed ECNN consistently and significantly outperforms the existing methods. |
| WOS关键词 | RECOGNITION ; IMAGES ; TEXT |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000382877500009 |
| 资助机构 | National Natural Science Foundation of China(61225009 ; National Basic Research Program of China(2012CB316304) ; Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(IDHT20140224) ; 61303173 ; 61432019 ; 61572498 ; 61532009 ; 61472379 ; 61572296) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12631]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 作者单位 | National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Yang, Xiaoshan,Zhang, Tianzhu,Xu, Changsheng. Semantic Feature Mining for Video Event Understanding[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2016,12(4):55:1-55:22. |
| APA | Yang, Xiaoshan,Zhang, Tianzhu,&Xu, Changsheng.(2016).Semantic Feature Mining for Video Event Understanding.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,12(4),55:1-55:22. |
| MLA | Yang, Xiaoshan,et al."Semantic Feature Mining for Video Event Understanding".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 12.4(2016):55:1-55:22. |
入库方式： OAI收割
来源：自动化研究所
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