### 抜粋

We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers. This is a diagnostic method that uses random sampling like RANSAC, but adaptively estimates the inlier scale using a novel adaptive scale estimator. The residual distribution model of inliers is assumed known, such as a Gaussian distribution. Given a putative solution, our inlier scale estimator attempts to extract a distribution for the inliers from the distribution of all residuals. This is done by globally searching a partition of the total distribution that best fits the Gaussian distribution. Then, the density of the residuals of estimated inliers is used as the score in the objective function to evaluate the putative solution. The output of the estimator is the best solution that gives the highest score. Experiments with various simulations and real data for line fitting and fundamental matrix estimation are carried out to validate our algorithm, which performs better than several of the latest robust estimators.

元の言語 | 英語 |
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ホスト出版物のタイトル | Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers |

ページ | 287-298 |

ページ数 | 12 |

エディション | PART 3 |

DOI | |

出版物ステータス | 出版済み - 2010 |

イベント | 9th Asian Conference on Computer Vision, ACCV 2009 - Xi'an, 中国 継続期間: 9 23 2009 → 9 27 2009 |

### 出版物シリーズ

名前 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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番号 | PART 3 |

巻 | 5996 LNCS |

ISSN（印刷物） | 0302-9743 |

ISSN（電子版） | 1611-3349 |

### その他

その他 | 9th Asian Conference on Computer Vision, ACCV 2009 |
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国 | 中国 |

市 | Xi'an |

期間 | 9/23/09 → 9/27/09 |

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

## フィンガープリント Adaptive-scale robust estimator using distribution model fitting' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

## これを引用

*Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers*(PART 3 版, pp. 287-298). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 5996 LNCS, 番号 PART 3). https://doi.org/10.1007/978-3-642-12297-2_28