LF-PGVIO: 点と測地線分を用いた広視野カメラ向け視覚慣性オドメトリフレームワーク
LF-PGVIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras using Points and Geodesic Segments
広視野・負平面視野のカメラでも使えるよう、全方向曲線検出と測地線分の点・線特徴を統合した視覚慣性オドメトリを提案し、公開データセットで高精度・高ロバスト性を示した。
著者: Ze Wang, Kailun Yang, Hao Shi, Yufan Zhang, Zhijie Xu, Fei Gao, Kaiwei Wang
分類: cs.CV, cs.RO, eess.IV
原文アブストラクト
In this paper, we propose LF-PGVIO, a Visual-Inertial-Odometry (VIO) framework for large Field-of-View (FoV) cameras with a negative plane using points and geodesic segments. The purpose of our research is to unleash the potential of point-line odometry with large-FoV omnidirectional cameras, even for cameras with negative-plane FoV. To achieve this, we propose an Omnidirectional Curve Segment Detection (OCSD) method combined with a camera model which is applicable to images with large distortions, such as panoramic annular images, fisheye images, and various panoramic images. The geodesic segment is sliced into multiple straight-line segments based on the radian and descriptors are extracted and recombined. Descriptor matching establishes the constraint relationship between 3D line segments in multiple frames. In our VIO system, line feature residual is also extended to support large-FoV cameras. Extensive evaluations on public datasets demonstrate the superior accuracy and robustness of LF-PGVIO compared to state-of-the-art methods. The source code will be made publicly available at https://github.com/flysoaryun/LF-PGVIO.
