Search Results for author:
Found 12 papers, 7 papers with code
PCR-99: A Practical Method for Point Cloud Registration with 99% Outliers
We propose a robust method for point cloud registration that can handle both unknown scales and extreme outlier ratios.
Robust Single Rotation Averaging Revisited
In this work, we propose a novel method for robust single rotation averaging that can efficiently handle an extremely large fraction of outliers.
What's Wrong with the Absolute Trajectory Error?
This metric is an attractive alternative to the ATE, in that it is capable of discerning the varying trajectory accuracy as the inlier trajectory error or the number of outliers varies.
HARA: A Hierarchical Approach for Robust Rotation Averaging
We propose a novel hierarchical approach for multiple rotation averaging, dubbed HARA.
Rotation-Only Bundle Adjustment
We propose a novel method for estimating the global rotations of the cameras independently of their positions and the scene structure.
Geometric Interpretations of the Normalized Epipolar Error
In this work, we provide geometric interpretations of the normalized epipolar error.
Robust Uncertainty-Aware Multiview Triangulation
We propose a robust and efficient method for multiview triangulation and uncertainty estimation.
Robust Single Rotation Averaging
We propose a novel method for single rotation averaging using the Weiszfeld algorithm.
RGB-D Odometry and SLAM
The two topics are closely related, as the former aims to track the incremental camera motion with respect to a local map of the scene, and the latter to jointly estimate the camera trajectory and the global map with consistency.
Triangulation: Why Optimize?
We propose a novel alternative to the classic midpoint method that leads to significantly lower 2D errors and parallax errors.
Closed-Form Optimal Two-View Triangulation Based on Angular Errors
In this paper, we study closed-form optimal solutions to two-view triangulation with known internal calibration and pose.
Loosely-Coupled Semi-Direct Monocular SLAM
We propose a novel semi-direct approach for monocular simultaneous localization and mapping (SLAM) that combines the complementary strengths of direct and feature-based methods.
