Dynamic Parallel and Distributed Graph Cuts
文献类型：期刊论文
| 作者 | Yu, Miao1,2 ; Shen, Shuhan1,3; Hu, Zhanyi1,3,4
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| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
 |
| 出版日期 | 2016-12-01 |
| 卷号 | 25期号:12页码:5511-5525 |
| 关键词 | Graph Cuts Parallel Computation Convergence Markov Random Field |
| DOI | 10.1109/TIP.2016.2609819 |
| 文献子类 | Article |
| 英文摘要 | Graph cuts are widely used in computer vision. To speed up the optimization process and improve the scalability for large graphs, Strandmark and Kahl introduced a splitting method to split a graph into multiple subgraphs for parallel computation in both shared and distributed memory models. However, this parallel algorithm (the parallel BK-algorithm) does not have a polynomial bound on the number of iterations and is found to be non-convergent in some cases due to the possible multiple optimal solutions of its sub-problems. To remedy this non-convergence problem, in this paper, we first introduce a merging method capable of merging any number of those adjacent sub-graphs that can hardly reach agreement on their overlapping regions in the parallel BK-algorithm. Based on the pseudo-boolean representations of graph cuts, our merging method is shown to be effectively reused all the computed flows in these sub-graphs. Through both splitting and merging, we further propose a dynamic parallel and distributed graph cuts algorithm with guaranteed convergence to the globally optimal solutions within a predefined number of iterations. In essence, this paper provides a general framework to allow more sophisticated splitting and merging strategies to be employed to further boost performance. Our dynamic parallel algorithm is validated with extensive experimental results. |
| WOS关键词 | MAXIMUM-FLOW PROBLEM ; MARKOV RANDOM-FIELDS ; ENERGY MINIMIZATION ; ALGORITHM |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000388205100001 |
| 资助机构 | National Natural Science Foundation of China(61333015 ; 61421004 ; 61473292) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13350]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_机器人视觉团队 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Zhongyuan Univ Technol, Zhengzhou 450007, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Miao,Shen, Shuhan,Hu, Zhanyi. Dynamic Parallel and Distributed Graph Cuts[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2016,25(12):5511-5525. |
| APA | Yu, Miao,Shen, Shuhan,&Hu, Zhanyi.(2016).Dynamic Parallel and Distributed Graph Cuts.IEEE TRANSACTIONS ON IMAGE PROCESSING,25(12),5511-5525. |
| MLA | Yu, Miao,et al."Dynamic Parallel and Distributed Graph Cuts".IEEE TRANSACTIONS ON IMAGE PROCESSING 25.12(2016):5511-5525. |
入库方式： OAI收割
来源：自动化研究所
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