Point cloud registration is a research field where the spatial relationship between two or
more sets of points in space is determined. Point clouds are found in multiple applications …

A point cloud as a collection of points is poised to bring about a revolution in acquiring and
generating three‐dimensional (3D) surface information of an object in 3D reconstruction …

This paper proposes a novel local feature descriptor, called a local feature statistics
histogram (LFSH), for efficient 3D point cloud registration. An LFSH forms a comprehensive …

Robots-operating autonomous assembly applications in an unstructured environment
require precise methods to locate the building components on site. However, the current …

Robots equipped with the vision systems at the end-effector provide a powerful combination
in industrial contexts, allowing to execute a wide range of manufacturing tasks, such as …

Facial recognition has attracted more and more attention since the rapid growth of artificial
intelligence (AI) techniques in recent years. However, most of the related works about facial …

Point cloud registration (PCR) is a vital problem in remote sensing and computer vision,
which has various important applications, such as 3D reconstruction, object recognition, and …

Currently, state-of-the-art methods for 3D object recognition rely in a deep learning-pipeline.
Nonetheless, these methods require a large amount of data that is not easy to obtain. In …

We present LiSTA (LiDAR Spatio-Temporal Analysis), a system to detect probabilistic object-
level change over time using multi-mission SLAM. Many applications require such a system …

With the development of autonomous driving, augmented reality, and other fields, it is
becoming increasingly important for machines to more accurately and comprehensively …