QuadricSLAM: 物体検出をランドマークとした二重二次曲面による物体指向SLAM
QuadricSLAM: Dual Quadrics from Object Detections as Landmarks in Object-oriented SLAM
複数視点の2D物体検出から各物体の3D二次曲面とカメラ位置を同時推定するSLAM手法を提案し、部分遮蔽に対応した検出器センサーモデルと因子グラフ最適化を実現した。
著者: Lachlan Nicholson, Michael Milford, Niko Sünderhauf
分類: cs.RO
原文アブストラクト
In this paper, we use 2D object detections from multiple views to simultaneously estimate a 3D quadric surface for each object and localize the camera position. We derive a SLAM formulation that uses dual quadrics as 3D landmark representations, exploiting their ability to compactly represent the size, position and orientation of an object, and show how 2D object detections can directly constrain the quadric parameters via a novel geometric error formulation. We develop a sensor model for object detectors that addresses the challenge of partially visible objects, and demonstrate how to jointly estimate the camera pose and constrained dual quadric parameters in factor graph based SLAM with a general perspective camera.
関連論文
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