首页> 外文会议>European Conference on Computer Vision >Representing Edge Models via Local Principal COmponent Analysis
【24h】

Representing Edge Models via Local Principal COmponent Analysis

机译:通过本地主成分分析代表边缘模型

获取原文

摘要

Edge detection depends not only upon the assumed model of what an edge is, but also on how this model is represented. The problem of how to represent the edge model is typically neglected, despite the fact that the representation is a bottleneck for both computational cost and accuracy. We propose to represent edge models by a partition of the edge manifold corresponding to the edge model, where each local element of the partition is described by its principal components. We describe the construction of this representation and demonstrate its benefits for various edge models.
机译:边缘检测不仅取决于所假设的边缘的模型,还取决于该模型的表示方式。尽管表示是计算成本和准确性的瓶颈,但通常忽略了如何代表边缘模型的问题。我们建议通过对应于边缘模型的边缘歧管的分区来表示边缘模型,其中分区的每个本地元素由其主组件描述。我们描述了这种代表的构建,并展示了其对各种边缘模型的好处。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号