Point clouds provide a flexible geometric representation suitable for countless applications
in computer graphics; they also comprise the raw output of most 3D data acquisition devices …

Higher dimensional data such as video and 3D are the leading edge of multimedia retrieval
and computer vision research. In this survey, we give a comprehensive overview and key …

Abstract 3D object recognition and pattern recognition are active and fast-growing research
areas in the field of computer vision. It is mandatory to define the pattern class, feature …

3D object recognition in cluttered scenes is a rapidly growing research area. Based on the
used types of features, 3D object recognition methods can broadly be divided into two …

In this paper, we present a novel global descriptor M2DP for 3D point clouds, and apply it to
the problem of loop closure detection. In M2DP, we project a 3D point cloud to multiple 2D …

This paper addresses the problem of compression of 3D point cloud sequences that are
characterized by moving 3D positions and color attributes. As temporally successive point …

LiDAR-based SLAM system is admittedly more accurate and stable than others, while its
loop closure detection is still an open issue. With the development of 3D semantic …

One core challenge in object pose estimation is to ensure accurate and robust performance
for large numbers of diverse foreground objects amidst complex background clutter. In this …

Place recognition is a challenging problem in mobile robotics, especially in unstructured
environments or under viewpoint and illumination changes. Most LiDAR-based methods rely …

Global localization is essential for robot navigation, of which the first step is to retrieve a
query from the map database. This problem is called place recognition. In recent years …