Improving video foreground segmentation with an object-like pool
文献类型：期刊论文
| 作者 | Cheng, Xiaoliu1,2; Lv, Wei1; Liu, Huawei1,2; You, Xing1; Li, Baoqing1; Yuan, Xiaobing1 |
| 刊名 | Journal of electronic imaging
 |
| 出版日期 | 2015-03-01 |
| 卷号 | 24期号:2页码:8 |
| ISSN号 | 1017-9909 |
| 关键词 | Video foreground segmentation Object-like pool Unsupervised Unlabeled Conditional random field Probabilistic superpixels |
| DOI | 10.1117/1.jei.24.2.023034 |
| 通讯作者 | You, xing() |
| 英文摘要 | Foreground segmentation in video frames is quite valuable for object and activity recognition, while the existing approaches often demand training data or initial annotation, which is expensive and inconvenient. we propose an automatic and unsupervised method of foreground segmentation given an unlabeled and short video. the pixel-level optical flow and binary mask features are converted into the normal probabilistic superpixels, therefore, they are adaptable to build the superpixel-level conditional random field which aims to label the foreground and background. we exploit the fact that the appearance and motion features of the moving object are temporally and spatially coherent in general, to construct an object-like pool and background-like pool via the previous segmented results. the continuously updated pools can be regarded as the "prior" knowledge of the current frame to provide a reliable way to learn the features of the object. experimental results demonstrate that our approach exceeds the current methods, both qualitatively and quantitatively. (c) the authors. |
| WOS关键词 | ROBUST SUPERPIXEL TRACKING ; CONDITIONAL RANDOM-FIELDS ; GRAPH CUTS ; ENERGY MINIMIZATION ; REGIONS ; SHAPE |
| WOS研究方向 | Engineering ; Optics ; Imaging Science & Photographic Technology |
| WOS类目 | Engineering, Electrical & Electronic ; Optics ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | IS&T & SPIE |
| WOS记录号 | WOS:000354873600034 |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2376521 |
| 专题 | 中国科学院大学 |
| 通讯作者 | You, Xing |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Wireless Sensor Network Lab, Shanghai 200050, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cheng, Xiaoliu,Lv, Wei,Liu, Huawei,et al. Improving video foreground segmentation with an object-like pool[J]. Journal of electronic imaging,2015,24(2):8. |
| APA | Cheng, Xiaoliu,Lv, Wei,Liu, Huawei,You, Xing,Li, Baoqing,&Yuan, Xiaobing.(2015).Improving video foreground segmentation with an object-like pool.Journal of electronic imaging,24(2),8. |
| MLA | Cheng, Xiaoliu,et al."Improving video foreground segmentation with an object-like pool".Journal of electronic imaging 24.2(2015):8. |
入库方式： iSwitch采集
来源：中国科学院大学
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