Video Anomaly Detection based on a Hierarchical Activity Discovery within Spatio-Temporal Contexts
文献类型：期刊论文
| 作者 | Xu, Dan; Song, Rui; Wu, Xinyu; Li, Nannan; Feng, Wei; Qian, Huihuan |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2014 |
| 英文摘要 | In this paper, we present a novel approach for video-anomaly detection in crowded and complicated scenes. The proposed approach detects anomalies based on a hierarchical activity-pattern discovery framework, comprehensively considering both global and local spatio-temporal contexts. The discovery is a coarse-to-fine learning process with unsupervised methods for automatically constructing normal activity patterns at different levels. A unified anomaly energy function is designed based on these discovered activity patterns to identify the abnormal level of an input motion pattern. We demonstrate the effectiveness of the proposed method on the UCSD anomaly-detection datasets and compare the performance with existing work. |
| 收录类别 | SCI |
| 原文出处 | http://www.sciencedirect.com/science/article/pii/S092523121400753X |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5443]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | NEUROCOMPUTING |
| 推荐引用方式 GB/T 7714 | Xu, Dan,Song, Rui,Wu, Xinyu,et al. Video Anomaly Detection based on a Hierarchical Activity Discovery within Spatio-Temporal Contexts[J]. NEUROCOMPUTING,2014. |
| APA | Xu, Dan,Song, Rui,Wu, Xinyu,Li, Nannan,Feng, Wei,&Qian, Huihuan.(2014).Video Anomaly Detection based on a Hierarchical Activity Discovery within Spatio-Temporal Contexts.NEUROCOMPUTING. |
| MLA | Xu, Dan,et al."Video Anomaly Detection based on a Hierarchical Activity Discovery within Spatio-Temporal Contexts".NEUROCOMPUTING (2014). |
入库方式： OAI收割
来源：深圳先进技术研究院
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