Computation of discrete Fréchet distance using CNN

Sook Yoon, H. Yoo, Sanghoon Yang, D. Park
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引用次数: 5

Abstract

The discrete Frechet distance basically measures the similarity of two curves considering their paths as well as distances of all discrete points on two curves. The present algorithms to compute the discrete Frechet distance between two curves have very high computational complexity. In order to reduce its computational burden, we propose a CNN architecture to compute the discrete Frechet Distance, employing the parallel processing capability of CNN consisting of an array of locally-coupled cells and each cell as a dynamical system. This paper presents the proposed CNN structure and its required cell coupling laws. The performance of the proposed system is verified through simulations.
用CNN计算离散帧间距离
离散Frechet距离基本上是衡量两条曲线的相似性,考虑它们的路径以及两条曲线上所有离散点的距离。目前计算曲线间离散Frechet距离的算法计算量非常大。为了减少计算负担,我们提出了一种计算离散Frechet距离的CNN架构,利用由一组局部耦合单元组成的CNN并行处理能力,每个单元都是一个动态系统。本文给出了所提出的CNN结构及其所需的单元耦合律。通过仿真验证了该系统的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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