3D位置合わせのための再帰的ロバストフィルタリング手法
A recursive robust filtering approach for 3D registration
センサノイズや特徴点位置の不確実性に強い、再帰的ロバストフィルタリングによる特徴ベース3D位置合わせ手法を提案し、実データと合成データで検証した。
著者: Abdenour Amamra, Nabil Aouf, Dowling Stuart, Mark Richardson
分類: cs.CV, cs.RO, cs.SY, eess.SY
原文アブストラクト
This work presents a new recursive robust filtering approach for feature-based 3D registration. Unlike the common state-of-the-art alignment algorithms, the proposed method has four advantages that have not yet occurred altogether in any previous solution. For instance, it is able to deal with inherent noise contaminating sensory data; it is robust to uncertainties caused by noisy feature localisation; it also combines the advantages of both (Formula presented.) and (Formula presented.) norms for a higher performance and a more prospective prevention of local minima. The result is an accurate and stable rigid body transformation. The latter enables a thorough control over the convergence regarding the alignment as well as a correct assessment of the quality of registration. The mathematical rationale behind the proposed approach is explained, and the results are validated on physical and synthetic data.
