论文标题
从多个2D/3D椭圆形的相对方差的基于设置的相机姿势估计
Level Set-Based Camera Pose Estimation From Multiple 2D/3D Ellipse-Ellipsoid Correspondences
论文作者
论文摘要
在本文中，我们提出了一个基于对象的相机姿势构成单个RGB图像和以椭圆形模型为代表的对象图的预构建图。我们表明，与点对应关系相反，成本函数的定义表征了3D对象对2D对象检测的投影并不简单。我们根据水平集采样开发了椭圆形成本，展示了其处理部分可见对象并将其性能与其他常见指标进行比较的属性。最后，我们表明，在检测到的椭圆上使用预测性不确定性允许对对应关系的贡献进行公平的权衡，从而改善了计算的姿势。该代码在https://gitlab.inria.fr/tangram/level-set基于camera-pose-Estimation上发布。
In this paper, we propose an object-based camera pose estimation from a single RGB image and a pre-built map of objects, represented with ellipsoidal models. We show that contrary to point correspondences, the definition of a cost function characterizing the projection of a 3D object onto a 2D object detection is not straightforward. We develop an ellipse-ellipse cost based on level sets sampling, demonstrate its nice properties for handling partially visible objects and compare its performance with other common metrics. Finally, we show that the use of a predictive uncertainty on the detected ellipses allows a fair weighting of the contribution of the correspondences which improves the computed pose. The code is released at https://gitlab.inria.fr/tangram/level-set-based-camera-pose-estimation.
