Incrementally Detecting Moving Objects in Video with Sparsity and Connectivity
文献类型：期刊论文
| 作者 | Pan, Jing1,2; Li, Xiaoli1; Li, Xuelong3 ; Pang, Yanwei1
|
| 刊名 | cognitive computation
 |
| 出版日期 | 2016-06-01 |
| 卷号 | 8期号:3页码:420-428 |
| 关键词 | Subspace learning Object detection Sparsity Connectivity |
| ISSN号 | 1866-9956 |
| 产权排序 | 3 |
| 英文摘要 | moving object detection is crucial for cognitive vision-based robot tasks. however, due to noise, dynamic background, variations in illumination, and high frame rate, it is a challenging task to robustly and efficiently detect moving objects in video using the clue of motion. state-of-the-art batch-based methods view a sequence of images as a whole and then model the background and foreground together with the constraints of foreground sparsity and connectivity (smoothness) in a unified framework. but the efficiency of the batch-based methods is very low. state-of-the-art incremental methods model the background by a subspace whose bases are updated frame by frame. however, such incremental methods do not make full use of the foreground sparsity and connectivity. in this paper, we develop an incremental method for detecting moving objects in video. compared to existing methods, the proposed method not only incrementally models the subspace for background reconstruction but also takes into account the sparsity and connectivity of the foreground. the optimization of the model is very efficient. experimental results on nine public videos demonstrate that the proposed method is much efficient than the state-of-the-art batch methods and has higher f1-score than the state-of-the-art incremental methods. |
| WOS标题词 | science & technology ; technology ; life sciences & biomedicine |
| 类目[WOS] | computer science, artificial intelligence ; neurosciences |
| 研究领域[WOS] | computer science ; neurosciences & neurology |
| 关键词[WOS] | surveillance ; model |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000376284900003 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/28136]  |
| 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 | 1.Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China 2.Tianjin Univ Technol & Educ, Sch Elect Engn, Tianjin 300222, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pan, Jing,Li, Xiaoli,Li, Xuelong,et al. Incrementally Detecting Moving Objects in Video with Sparsity and Connectivity[J]. cognitive computation,2016,8(3):420-428. |
| APA | Pan, Jing,Li, Xiaoli,Li, Xuelong,&Pang, Yanwei.(2016).Incrementally Detecting Moving Objects in Video with Sparsity and Connectivity.cognitive computation,8(3),420-428. |
| MLA | Pan, Jing,et al."Incrementally Detecting Moving Objects in Video with Sparsity and Connectivity".cognitive computation 8.3(2016):420-428. |
入库方式： OAI收割
来源：西安光学精密机械研究所
浏览0
下载0
收藏0
其他版本
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。