KISS-Matcher: 高速でロバストな点群位置合わせの再考
KISS-Matcher: Fast and Robust Point Cloud Registration Revisited
点群位置合わせのための新しい特徴検出器Faster-PFHとk-coreベースのグラフ枝刈りを組み合わせ、高速かつ高精度なオープンソースC++ライブラリKISS-Matcherを開発した。
著者: Hyungtae Lim, Daebeom Kim, Gunhee Shin, Jingnan Shi, Ignacio Vizzo, Hyun Myung, Jaesik Park, Luca Carlone
分類: cs.CV, cs.RO
原文アブストラクト
While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theoretic pruning, or pose solvers. In this paper, we take a holistic view on the registration problem and develop an open-source and versatile C++ library for point cloud registration, called KISS-Matcher. KISS-Matcher combines a novel feature detector, Faster-PFH, that improves over the classical fast point feature histogram (FPFH). Moreover, it adopts a $k$-core-based graph-theoretic pruning to reduce the time complexity of rejecting outlier correspondences. Finally, it combines these modules in a complete, user-friendly, and ready-to-use pipeline. As verified by extensive experiments, KISS-Matcher has superior scalability and broad applicability, achieving a substantial speed-up compared to state-of-the-art outlier-robust registration pipelines while preserving accuracy. Our code will be available at https://github.com/MIT-SPARK/KISS-Matcher.
