63 citations · 95 across the 15 of their papers we have counts for
16 papers
Non-Minimal Sampling and Consensus for Prohibitively Large Datasets
Seong Hun Lee, Patrick Vandewalle, Javier Civera
We introduce NONSAC (Non-Minimal Sampling and Consensus), a general framework for robust and scalable model estimation from arbitrarily large datasets contaminated with noise and o…
An Efficient Closed-Form Solution to Full Visual-Inertial State Initialization
Samuel Cerezo, Seong Hun Lee, Javier Civera
In this letter, we present a closed-form initialization method that recovers the full visual-inertial state without nonlinear optimization. Unlike previous approaches that rely on…
P3P Made Easy
Seong Hun Lee, Patrick Vandewalle, Javier Civera
We revisit the classical Perspective-Three-Point (P3P) problem, which aims to recover the absolute pose of a calibrated camera from three 2D-3D correspondences. It has long been kn…
Alignment Scores: Robust Metrics for Multiview Pose Accuracy Evaluation
Seong Hun Lee, Javier Civera
We propose three novel metrics for evaluating the accuracy of a set of estimated camera poses given the ground truth: Translation Alignment Score (TAS), Rotation Alignment Score (R…
PCR-99: A Practical Method for Point Cloud Registration with 99 Percent Outliers
Seong Hun Lee, Javier Civera, Patrick Vandewalle
We propose a robust method for point cloud registration that can handle both unknown scales and extreme outlier ratios. Our method, dubbed PCR-99, uses a deterministic 3-point samp…
Robust Single Rotation Averaging Revisited
Seong Hun Lee, Javier Civera
In this work, we propose a novel method for robust single rotation averaging that can efficiently handle an extremely large fraction of outliers. Our approach is to minimize the to…
What's Wrong with the Absolute Trajectory Error?
Seong Hun Lee, Javier Civera
One of the limitations of the commonly used Absolute Trajectory Error (ATE) is that it is highly sensitive to outliers. As a result, in the presence of just a few outliers, it ofte…
RODIAN: Robustified Median
Seong Hun Lee, Javier Civera
We propose a robust method for averaging numbers contaminated by a large proportion of outliers. Our method, dubbed RODIAN, is inspired by the key idea of MINPRAN [1]: We assume th…
HARA: A Hierarchical Approach for Robust Rotation Averaging
Seong Hun Lee, Javier Civera
We propose a novel hierarchical approach for multiple rotation averaging, dubbed HARA. Our method incrementally initializes the rotation graph based on a hierarchy of triplet suppo…
Rotation-Only Bundle Adjustment
Seong Hun Lee, Javier Civera
We propose a novel method for estimating the global rotations of the cameras independently of their positions and the scene structure. When two calibrated cameras observe five or m…
Robust Uncertainty-Aware Multiview Triangulation
Seong Hun Lee, Javier Civera
We propose a robust and efficient method for multiview triangulation and uncertainty estimation. Our contribution is threefold: First, we propose an outlier rejection scheme using…
Geometric Interpretations of the Normalized Epipolar Error
Seong Hun Lee, Javier Civera
In this work, we provide geometric interpretations of the normalized epipolar error. Most notably, we show that it is directly related to the following quantities: (1) the shortest…
Robust Single Rotation Averaging
Seong Hun Lee, Javier Civera
We propose a novel method for single rotation averaging using the Weiszfeld algorithm. Our contribution is threefold: First, we propose a robust initialization based on the element…
RGB-D Odometry and SLAM
Javier Civera, Seong Hun Lee
The emergence of modern RGB-D sensors had a significant impact in many application fields, including robotics, augmented reality (AR) and 3D scanning. They are low-cost, low-power…
Triangulation: Why Optimize?
Seong Hun Lee, Javier Civera
For decades, it has been widely accepted that the gold standard for two-view triangulation is to minimize the cost based on reprojection errors. In this work, we challenge this ide…
Loosely-Coupled Semi-Direct Monocular SLAM
Seong Hun Lee, Javier Civera
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. Th…