Image Based 6-DOF Camera Pose Estimation with Weighted RANSAC 3D
نویسنده
چکیده
In this work an approach for image based 6-DOF pose estimation, with respect to a given 3D point cloud model, is presented. We use 3D annotated training views of the model from which we extract natural 2D features, which can be matched to the query image 2D features. In the next step typically the Perspective-N-Point Problem in combination with the popular RANSAC algorithm on the given 2D-3D point correspondences is used, to estimate the 6-D pose of the camera in respect to the model. We propose a novel extension of the RANSAC algorithm, named w-RANSAC 3D, which uses known 3D information to weight each match individually. The evaluation shows that w-RANSAC 3D leads to a more robust pose estimation while needing significantly less iterations.
منابع مشابه
6-DOF Pose Estimation of an Autonomous Car by Visual Feature Correspondence and Tracking
This paper presents a pose estimation method based on 1-Point RANSAC EKF (Extended Kalman Filter) framework. The method fuses the depth data from a LIDAR and the visual data from a monocular camera to estimate the pose of an Unmanned Ground Vehicle (UGV) in a GPS denied environment. Its estimation framework continually updates the vehicle’s 6D pose state and temporary estimates of the extracted...
متن کاملWorldwide Pose Estimation Using 3D Point Clouds
We address the problem of determining where a photo was taken by estimating a full 6-DOF-plus-intrincs camera pose with respect to a large geo-registered 3D point cloud, bringing together research on image localization, landmark recognition, and 3D pose estimation. Our method scales to datasets with hundreds of thousands of images and tens of millions of 3D points through the use of two new tec...
متن کاملCamera 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...
متن کاملRobust Large-Scale Localization in 3D Point Clouds Revisited
We tackle the problem of getting a full 6-DOF pose estimation of a query image inside a given point cloud. This technical report re-evaluates the algorithms proposed by Y. Li et al. “Worldwide Pose Estimation using 3D Point Cloud” [1]. Our code computes poses from 3 or 4 points, with both known and unknown focal length. The results can easily be displayed and analyzed with Meshlab. We found bot...
متن کاملQuadrotor control using dual camera visual feedback
In this paper, a vision-based stabilization and output tracking control method for a four-rotor helicopter has been proposed. A novel 2 camera method has been described for estimating the full 6 DOF pose of the helicopter. This two camera system is consisting of a pan-tilt ground camera and an onboard camera. The pose estimation algorithm is compared in simulation to other methods (such as four...
متن کامل