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Sparse line-optical flow field computing method based on lines matching

  • Zhen Yu Guan
  • , Jie Li
  • , Huan Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper brings out a new sparse line-optical flow field computing method. Firstly, we establish a lines matching algorithm based on Kalman Filter (KF). In this algorithm, we map lines in an image into Hough space, after that we employ KF to predict the position in the following frame in order to match lines in image sequence. Secondly, we present the concept of sparse line-optical flow field of images and propose the calculation method of it. By using the camera perspective projection model and the optical flow Identity, we can get the sparse line-optical flow field. Simulations is made in the following step, and results show that the lines matching algorithm works well and the accuracy of the calculation method proposed in this paper is as good as that of the classic Horn algorithm, while the calculating time-cost of it is only 1/30 Horn algorithm's.

Original languageEnglish
Title of host publicationFrontiers of Manufacturing and Design Science IV
Pages2099-2107
Number of pages9
DOIs
Publication statusPublished - 2014
Event4th International Conference on Frontiers of Manufacturing and Design Science, ICFMD 2013 - Hong Kong, China
Duration: 10 Sept 201312 Sept 2013

Publication series

NameApplied Mechanics and Materials
Volume496-500
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference4th International Conference on Frontiers of Manufacturing and Design Science, ICFMD 2013
Country/TerritoryChina
CityHong Kong
Period10/09/1312/09/13

Keywords

  • Camera perspective projection model
  • Kalman filter
  • Lines matching
  • Sparse line-optical flow field

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