ハイブリッドICP：データ対応付けと誤差指標を動的に最適化するICP
Hybrid ICP
物体の画像と現在の推定値に基づいてデータ対応付け手法と誤差指標を動的に切り替えるICPの新手法を提案し、物体姿勢推定の精度とノイズ頑健性の向上を示した。
著者: Kamil Dreczkowski, Edward Johns
分類: cs.CV, cs.RO
原文アブストラクト
ICP algorithms typically involve a fixed choice of data association method and a fixed choice of error metric. In this paper, we propose Hybrid ICP, a novel and flexible ICP variant which dynamically optimises both the data association method and error metric based on the live image of an object and the current ICP estimate. We show that when used for object pose estimation, Hybrid ICP is more accurate and more robust to noise than other commonly used ICP variants. We also consider the setting where ICP is applied sequentially with a moving camera, and we study the trade-off between the accuracy of each ICP estimate and the number of ICP estimates available within a fixed amount of time.
