Knowledge Commons of Institute of Automation,CAS
Deep Structured Event Modeling for User-Generated Photos | |
Yang, Xiaoshan1,2![]() ![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON MULTIMEDIA
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2018 | |
卷号 | 20期号:8页码:2100-2113 |
摘要 | Vision based event analysis plays a very critical role in automatically organizing user generated photos. It is difficult because of the following challenges. (1) Intra-class variation. Photos uploaded by users are sparsely sampled visual appearances of event over time. Thus, each photo may only capture a single object or scene of a specific complex event. (2) Inter-class confusion. Photos related to different events may contain similar objects or scenes. (3) For abnormal event, it has sample scarcity issue and only few samples can be used for event pattern learning. In this paper, by considering the photo taken time, we propose a novel structured event modeling (SEM) framework for event analysis by exploiting temporal information of visual features and event classes in photo sequence. More specifically, the temporal event patterns of the photo sequence and the relationship of different photos are learned jointly through deep neural networks (CNNs and RNNs) and conditional random field (CRF). We evaluate the proposed structured event modeling framework in two applications including the mutliclass event recognition and abnormal event discovery in photo sequence. The extensive experimental results on a public event recognition dataset and a collected abnormal event dataset demonstrate the effectiveness of the proposed method. |
关键词 | Event Analysis Unusual Event Detection Deep Learning |
DOI | 10.1109/TMM.2017.2788210 |
收录类别 | SCI |
语种 | 英语 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/19702 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
作者单位 | 1.National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yang, Xiaoshan,Zhang, Tianzhu,Xu, Changsheng. Deep Structured Event Modeling for User-Generated Photos[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2018,20(8):2100-2113. |
APA | Yang, Xiaoshan,Zhang, Tianzhu,&Xu, Changsheng.(2018).Deep Structured Event Modeling for User-Generated Photos.IEEE TRANSACTIONS ON MULTIMEDIA,20(8),2100-2113. |
MLA | Yang, Xiaoshan,et al."Deep Structured Event Modeling for User-Generated Photos".IEEE TRANSACTIONS ON MULTIMEDIA 20.8(2018):2100-2113. |
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Deep-Structured Even(1164KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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