The capability of an active spacecraft to accurately estimate its relative position and attitude
(pose) with respect to an active/inactive, artificial/natural space object (target) orbiting in …

Virtual reality, augmented reality, robotics, and autonomous driving, have recently attracted
much attention from both academic and industrial communities, in which image-based …

The most recent trend in estimating the 6D pose of rigid objects has been to train deep
networks to either directly regress the pose from the image or to predict the 2D locations of …

Most recent 6D pose estimation frameworks first rely on a deep network to establish
correspondences between 3D object keypoints and 2D image locations and then use a …

This textbook on Photogrammetric Computer Vision–Statistics, Geometry, Orientation and
Reconstruction provides a statistical treatment of the geometry of multiple view analysis …

An approach for estimating the pose of a camera given a set of 3D points and their
corresponding 2D image projections is presented. It formulates the problem as a non-linear …

In this paper we deal with the camera pose estimation problem from a set of 2D/3D line
correspondences, which is also known as PnL (Perspective-n-Line) problem. We carry out …

Most recent 6D object pose estimation methods, including unsupervised ones, require many
real training images. Unfortunately, for some applications, such as those in space or deep …

Nonlinear estimation in robotics and vision is typically plagued with outliers due to wrong
data association or incorrect detections from signal processing and machine learning …

In this study, we propose a novel end-to-end system called Human–Machine Collaborative
Inspection (HMCI) to enable collaboration between inspectors with Mixed Reality (MR) …