Quasi-maximum feasible subsystem for geometric computer vision problems

Chanki Yu, Da Young Ju, Sang Wook Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


A robust fitting algorithm for geometric computer vision problems under the L∞-norm optimisation framework is presented. It is essentially based on the maximum feasible subsystem (MaxFS) but it overcomes the computational limitation of the MaxFS for large data by finding only a quasi-maximum feasible subset. Experimental results demonstrate that the algorithm removes outliers more effectively than the other parameter estimation methods recently developed when the outlier-to-inlier ratio in a data set is high.

Original languageEnglish
Pages (from-to)1071-1073
Number of pages3
JournalElectronics Letters
Issue number14
Publication statusPublished - 2015 Jul 9

Bibliographical note

Publisher Copyright:
© The Institution of Engineering and Technology 2015.

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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