With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual
(RGB) sensing has become available for widespread use. The complementary nature of the …

A key requirement for leveraging supervised deep learning methods is the availability of
large, labeled datasets. Unfortunately, in the context of RGB-D scene understanding, very …

This paper presents an object classification method for vision and light detection and
ranging (LIDAR) fusion of autonomous vehicles in the environment. This method is based on …

It is important to measure and analyze people behavior to design systems which interact
with people. This article describes a portable people behavior measurement system using a …

Although RGB-D sensors have enabled major breakthroughs for several vision tasks, such
as 3D reconstruction, we have not attained the same level of success in high-level scene …

Siamese network based trackers formulate 3D single object tracking as cross-correlation
learning between point features of a template and a search area. Due to the large …

Abstract 3D object tracking in point clouds is still a challenging problem due to the sparsity of
LiDAR points in dynamic environments. In this work, we propose a Siamese voxel-to-BEV …

Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers
or game consoles naturally through gestures and spoken commands without any other …

Point clouds are challenging to process due to their sparsity, therefore autonomous vehicles
rely more on appearance attributes than pure geometric features. However, 3D LIDAR …

Multiple human tracking (MHT) is a fundamental task in many computer vision applications.
Appearance‐based approaches, primarily formulated on RGB data, are constrained and …