Institute of Computing Technology, Chinese Academy IR
Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video | |
Li, Jia2,3; Tian, Yonghong1; Huang, Tiejun1; Gao, Wen1 | |
2010-11-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF COMPUTER VISION |
ISSN | 0920-5691 |
卷号 | 90期号:2页码:150-165 |
摘要 | In this paper, we present a probabilistic multi-task learning approach for visual saliency estimation in video. In our approach, the problem of visual saliency estimation is modeled by simultaneously considering the stimulus-driven and task-related factors in a probabilistic framework. In this framework, a stimulus-driven component simulates the low-level processes in human vision system using multi-scale wavelet decomposition and unbiased feature competition; while a task-related component simulates the high-level processes to bias the competition of the input features. Different from existing approaches, we propose a multi-task learning algorithm to learn the task-related "stimulus-saliency" mapping functions for each scene. The algorithm also learns various fusion strategies, which are used to integrate the stimulus-driven and task-related components to obtain the visual saliency. Extensive experiments were carried out on two public eye-fixation datasets and one regional saliency dataset. Experimental results show that our approach outperforms eight state-of-the-art approaches remarkably. |
关键词 | Visual saliency Probabilistic framework Visual search tasks Multi-task learning |
DOI | 10.1007/s11263-010-0354-6 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Chinese National Natural Science Foundation[60973055] ; Chinese National Natural Science Foundation[90820003] ; National Basic Research Program of China[2009CB320906] ; Fok Ying Dong Education Foundation[122008] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000281087900002 |
出版者 | SPRINGER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/12507 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Tian, Yonghong |
作者单位 | 1.Peking Univ, Natl Engn Lab Video Technol, Beijing 100871, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Jia,Tian, Yonghong,Huang, Tiejun,et al. Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2010,90(2):150-165. |
APA | Li, Jia,Tian, Yonghong,Huang, Tiejun,&Gao, Wen.(2010).Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video.INTERNATIONAL JOURNAL OF COMPUTER VISION,90(2),150-165. |
MLA | Li, Jia,et al."Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video".INTERNATIONAL JOURNAL OF COMPUTER VISION 90.2(2010):150-165. |
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