We propose the first fast and certifiable algorithm for the registration of two sets of three-
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …

We propose the first general and scalable framework to design certifiable algorithms for
robust geometric perception in the presence of outliers. Our first contribution is to show that …

We propose a robust approach for the registration of two sets of 3D points in the presence of
a large amount of outliers. Our first contribution is to reformulate the registration problem …

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 …

Finding relative pose between two calibrated images is a fundamental task in computer
vision. Given five point correspondences, the classical five-point methods can be used to …

This article presents a novel outlier rejection approach for feature-based visual odometry.
The proposed approach is based on an empirical observation that shows that some 2D–3D …

Abstract 3D correspondence ie a pair of 3D points is a fundamental concept in computer
vision. A set of 3D correspondences when equipped with compatibility edges forms a …

Spatial perception is the backbone of many robotics applications, and spans a broad range
of research problems, including localization and mapping, point cloud alignment, and …

Consensus maximization is one of the most widely used robust fitting paradigms in computer
vision, and the development of algorithms for consensus maximization is an active research …

Point cloud registration is an essential step for free-form blade reconstruction in industrial
measurement. Nonetheless, measuring defects of the 3-D acquisition system unavoidably …