CSpace  > 中国科学院计算技术研究所期刊论文  > 英文
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
ISSN0920-5691
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
DOI10.1007/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
被引频次:102[WOS]   [WOS记录]     [WOS相关记录]
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.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Li, Jia]的文章
[Tian, Yonghong]的文章
[Huang, Tiejun]的文章
百度学术
百度学术中相似的文章
[Li, Jia]的文章
[Tian, Yonghong]的文章
[Huang, Tiejun]的文章
必应学术
必应学术中相似的文章
[Li, Jia]的文章
[Tian, Yonghong]的文章
[Huang, Tiejun]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。