首页> 外文会议>International Conference on Intelligent Control and Information Processing >A missing data estimation approach for small size image sequence
【24h】

A missing data estimation approach for small size image sequence

机译:小尺寸图像序列的缺失数据估计方法

获取原文

摘要

Data missing is a frequently encountered problem for structure-from-motion (SFM). In this paper, a sub-sequence based approach is proposed to deal with the missing data estimation problem for small size image sequence. In the proposed method, the sub-sequences are first extracted from the original sequence. Further, multiple weaker estimators are constructed by means of the column space fitting (CSF) algorithm. Finally, the missing entries are estimated by a linear programming based weighted model. Experimental results on several widely used image sequences demonstrate the effectiveness and feasibility of the proposed algorithm.
机译:对于运动结构(SFM),数据丢失是一个经常遇到的问题。本文提出了一种基于子序列的方法来处理小尺寸图像序列的缺失数据估计问题。在提出的方法中,首先从原始序列中提取子序列。此外,借助于列空间拟合(CSF)算法构造了多个较弱的估计量。最后,通过基于线性规划的加权模型估计丢失的条目。在几种广泛使用的图像序列上的实验结果证明了该算法的有效性和可行性。

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