HYBRID CAMERA POSE ESTIMATION COMBINING SQUARE FIDUCIALS LOCALIZATION TECHNIQUE AND ORTHOGONAL ITERATION ALGORITHM

Hybrid Camera Pose Estimation Combining Square Fiducials Localization Technique and Orthogonal Iteration Algorithm

Hybrid camera pose estimation combining square fiducials localisation technique and orthogonal iteration algorithm

Camera pose estimation from video images is a fundamental problem in machine vision and Augmented Reality (AR) systems. Most developed solutions are either linear for both n points and n lines, or iterative depending on nonlinear optimization of some geometric constraints. In this paper, we first survey several existing methods and compare their performances in an AR context. Then, we present a...

Joint Camera Pose Estimation and 3D Human Pose Estimation in a Multi-camera Setup

In this paper we propose an approach to jointly perform camera pose estimation and human pose estimation from videos recorded by a set of cameras separated by wide baselines. Multi-camera pose estimation is very challenging in case of wide baselines or in general when patch-based feature correspondences are difficult to establish across images. For this reason, we propose to exploit the motion ...

Guided Sparse Camera Pose Estimation

In this paper, we present an idea for a sparse approach to calculate camera poses from RGB images and laser distance measurements to perform subsequent facade reconstruction. The core idea is to guide the image recording process by choosing distinctive features with the laser range finder, e.g. building or window corners. From these distinctive features, we can establish correspondences between...

Camera Pose Estimation in Unknown Environments using a Sequence of Wide-Baseline Monocular Images

In this paper, a feature-based technique for the camera pose estimation in a sequence of wide-baseline images has been proposed. Camera pose estimation is an important issue in many computer vision and robotics applications, such as, augmented reality and visual SLAM. The proposed method can track captured images taken by hand-held camera in room-sized workspaces with maximum scene depth of 3-4...