天津工业大学学报2017，Vol.36Issue(5)：74-78,5.DOI:10.3969/j.issn.1671-024x.2017.05.015
一种用于物体姿态估计的快速Isomap降维算法
A fast Isomap dimensionality reduction algorithm for object pose estimation
摘要
Abstract
In order to reduce the complexity of the dimensionality reduction in the object pose estimation algorithm based on manifold learning,and to improve the execution speed of the algorithm,a fast Isomap algorithm is proposed.By analyzing the calculation process of Isomap,it is found that calculating the geodesic distance between any two points is one of the reasons for its high computational complexity.Based on this analysis,it is assumed that the two images are adjacent,after dimensionality reduction,the corresponding data points are adjacent on the low-dimensional manifold, and then the Isomap can be improved by optimizing the calculation of the geodesic distance matrix.In this method,it is no longer necessary to traverse all the data points,which can greatly reduce the computational complexity of the algorithm.The experimental results show that by ensuring the performances, the efficiency of the proposed algorithm is improved, and the efficiency of the algorithm is highly improved, especially for long image sequences. When the number of images reached 350, the time cost of the proposed algorithm is 13% of the original method.关键词
流形学习/Isomap/姿态估计/非线性降维算法Key words
manifold learning/Isomap/pose estimation/nonlinear dimensionality reduction algorithm分类
信息技术与安全科学引用本文复制引用
汪剑鸣,张笑,王胜蓓..一种用于物体姿态估计的快速Isomap降维算法[J].天津工业大学学报,2017,36(5):74-78,5.基金项目
国家自然科学基金面上项目(61373104) （61373104）
