The loss function, also known as cost function, is used for training a neural network or other
machine learning models. Over the past decade, researchers have designed many loss …

Two images of a single scene/object are related by the epipolar geometry, which can be
described by a 3× 3 singular matrix called the essential matrix if images' internal parameters …

Multi-robot simultaneous localization and mapping (SLAM) is a crucial capability to obtain
timely situational awareness over large areas. Real-world applications demand multi-robot …

We present a generalization of the Cauchy/Lorentzian, Geman-McClure, Welsch/Leclerc,
generalized Charbonnier, Charbonnier/pseudo-Huber/L1-L2, and L2 loss functions. By …

A key aspect of robotics today is estimating the state (eg, position and orientation) of a robot,
based on noisy sensor data. This book targets students and practitioners of robotics by …

This article provides an elaborate overview of current research in extended object tracking.
We provide a clear definition of the extended object tracking problem and discuss its …

Abstract The Disk Substructures at High Angular Resolution Project (DSHARP) used ALMA
to map the 1.25 mm continuum of protoplanetary disks at a spatial resolution of∼ 5 au. We …

We investigate projective estimation under model inadequacies, ie, when the underpinning
assumptions of the projective model are not fully satisfied by the data. We focus on the task …

" This library is useful for practitioners, and is an excellent tool for those entering the field: it
is a set of computer vision algorithms that work as advertised."-William T. Freeman …

Plane segmentation is a basic task in the automatic reconstruction of indoor and urban
environments from unorganized point clouds acquired by laser scanners. As one of the most …