This paper aims to present a brief overview of the development of sensor fusion in various
application in recent years, and to understand the challenges and ability of sensor fusion …

Most of the existing deep learning-based methods for 3D hand and human pose estimation
from a single depth map are based on a common framework that takes a 2D depth map and …

Joint estimation of the human body is suitable for many fields such as human–computer
interaction, autonomous driving, video analysis and virtual reality. Although many depth …

We propose a new method to quickly and accurately predict 3D positions of body joints from
a single depth image, using no temporal information. We take an object recognition …

We propose a new method to quickly and accurately predict human pose---the 3D positions
of body joints---from a single depth image, without depending on information from preceding …

We describe two new approaches to human pose estimation. Both can quickly and
accurately predict the 3D positions of body joints from a single depth image without using …

We propose a viewpoint invariant model for 3D human pose estimation from a single depth
image. To achieve this, our discriminative model embeds local regions into a learned …

Markerless tracking of human pose is a hard yet relevant problem. In this paper, we derive
an efficient filtering algorithm for tracking human pose using a stream of monocular depth …

Interest in human-robot coexistence, in which humans and robots share a common work
volume, is increasing in manufacturing environments. Efficient work coordination requires …

We present a fast, automatic method for accurately capturing full-body motion data using a
single depth camera. At the core of our system lies a realtime registration process that …