Graph Degree Linkage:Agglomerative Clustering on a Directed Graph
文献类型：会议论文
| 作者 | Wei Zhang; Xiaogang Wang; Deli Zhao; Xiaoou Tang |
| 出版日期 | 2012 |
| 会议名称 | 12th European Conference on Computer Vision (ECCV) |
| 会议地点 | 意大利 |
| 英文摘要 | This paper proposes a simple but effective graph-based agglomerative algorithm, for clustering high-dimensional data. We explore the different roles of two fundamental concepts in graph theory, indegree and outdegree, in the context of clustering. The average indegree reflects the density near a sample, and the average outdegree characterizes the local geometry around a sample. Based on such insights, we define the affinity measure of clusters via the product of average indegree and average outdegree. The product-based affinity makes our algorithm robust to noise. The algorithm has three main advantages: good performance, easy implementation, and high computational efficiency. We test the algorithm on two fundamental computer vision problems: image clustering and object matching. Extensive experiments demonstrate that it outperforms the state-of-the-arts in both applications. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3790]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2012 |
| 推荐引用方式 GB/T 7714 | Wei Zhang,Xiaogang Wang,Deli Zhao,et al. Graph Degree Linkage:Agglomerative Clustering on a Directed Graph[C]. 见:12th European Conference on Computer Vision (ECCV) . 意大利. |
入库方式： OAI收割
来源：深圳先进技术研究院
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