NATAS: Neural Activity Trace Aware Saliency
文献类型：期刊论文
| 作者 | Zhu, Guokang ; Wang, Qi; Yuan, Yuan
|
| 刊名 | ieee transactions on cybernetics
 |
| 出版日期 | 2014-07-01 |
| 卷号 | 44期号:7页码:1014-1024 |
| 关键词 | Computer vision global contrast machine learning neural activity trace preactivation saliency detection visual attention |
| ISSN号 | 2168-2267 |
| 英文摘要 | saliency detection has raised much interest in computer vision recently. many visual saliency models have been developed for individual images, video clips, and image pairs. however, image sequence, one most general occasion in the real world, is not explored yet. a general image sequence is different from video clips whose temporal continuity is maintained and image pairs where common objects exist. it might contain some similar low-level properties while completely distinct contents. traditional saliency detection methods will fail on these general sequences. based on this consideration, this paper investigates the shortcomings of the classical saliency detection methods, which significantly limit their advantages: 1) inability to capture the natural connections among sequential images, 2) over-reliance on motion cues, and 3) restriction to image pairs/videos with common objects. in order to address these problems, we propose a framework that performs the following contributions: 1) construct an image data set as benchmark through a rigorously designed behavioral experiment, 2) propose a neural activity trace aware saliency model to capture the general connections among images, and 3) design a novel measure to handle the low-level clues contained among sequential images. experimental results demonstrate that the proposed saliency model is associated with a tremendous advancement compared with traditional methods when dealing with the general image sequence. |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | computer science, artificial intelligence ; computer science, cybernetics |
| 研究领域[WOS] | computer science |
| 关键词[WOS] | region detection ; object recognition ; visual-attention ; color ; memory ; segmentation ; perception ; images ; model |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000342225800003 |
| 公开日期 | 2015-03-18 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/22364]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Guokang,Wang, Qi,Yuan, Yuan. NATAS: Neural Activity Trace Aware Saliency[J]. ieee transactions on cybernetics,2014,44(7):1014-1024. |
| APA | Zhu, Guokang,Wang, Qi,&Yuan, Yuan.(2014).NATAS: Neural Activity Trace Aware Saliency.ieee transactions on cybernetics,44(7),1014-1024. |
| MLA | Zhu, Guokang,et al."NATAS: Neural Activity Trace Aware Saliency".ieee transactions on cybernetics 44.7(2014):1014-1024. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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